[REVIEW]: treesiftr: An R package and server for viewing phylogenetic trees and data

whedon commented 5 years ago

Submitting author: @wrightaprilm (April Wright) Repository: https://github.com/wrightaprilm/treesiftr Version: v1.0.0 Editor: @juanklopper Reviewer: @ethanwhite, @rachelss Archive: 10.5281/zenodo.2541824

Status

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Reviewers and authors:

Please avoid lengthy details of difficulties in the review thread. Instead, please create a new issue in the target repository and link to those issues (especially acceptance-blockers) in the review thread below. (For completists: if the target issue tracker is also on GitHub, linking the review thread in the issue or vice versa will create corresponding breadcrumb trails in the link target.)

Reviewer instructions & questions

@ethanwhite & @rachelss, please carry out your review in this issue by updating the checklist below. If you cannot edit the checklist please:

Make sure you're logged in to your GitHub account
Be sure to accept the invite at this URL: https://github.com/openjournals/jose-reviews/invitations

The reviewer guidelines are available here: https://jose.theoj.org/about#reviewer_guidelines. Any questions/concerns please let @juanklopper know.

Review checklist for @ethanwhite

Conflict of interest

[x] As the reviewer I confirm that I have read the JOSE conflict of interest policy and that there are no conflicts of interest for me to review this work.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSE code of conduct.

General checks

[x] Repository: Is the source for this learning module available at the repository url?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of a standard license? (OSI-approved for code, Creative Commons for content)
[x] Version: Does the release version given match the repository release (v1.0.0)?
[x] Authorship: Has the submitting author (@wrightaprilm) made visible contributions to the module? Does the full list of authors seem appropriate and complete?

Documentation

[x] A statement of need: Do the authors clearly state the need for this module and who the target audience is?
[x] Installation instructions: Is there a clearly stated list of dependencies?
[x] Usage: Does the documentation explain how someone would adopt the module, and include examples of how to use it?
[x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the module 2) Report issues or problems with the module 3) Seek support

Pedagogy / Instructional design (Work-in-progress: reviewers, please comment!)

[x] Learning objectives: Does the module make the learning objectives plainly clear? (We don't require explicitly written learning objectives; only that they be evident from content and design.)
[x] Content scope and length: Is the content substantial for learning a given topic? Is the length of the module appropriate?
[x] Pedagogy: Does the module seem easy to follow? Does it observe guidance on cognitive load? (working memory limits of 7 +/- 2 chunks of information)
[x] Content quality: Is the writing of good quality, concise, engaging? Are the code components well crafted? Does the module seem complete?
[x] Instructional design: Is the instructional design deliberate and apparent? For example, exploit worked-example effects; effective multi-media use; low extraneous cognitive load.

JOSE paper

[x] Authors: Does the paper.md file include a list of authors with their affiliations?
[x] A statement of need: Does the paper clearly state the need for this module and who the target audience is?
[x] Description: Does the paper describe the learning materials and sequence?
[x] Does it describe how it has been used in the classroom or other settings, and how someone might adopt it?
[x] Could someone else teach with this module, given the right expertise?
[x] Does the paper tell the "story" of how the authors came to develop it, or what their expertise is?
[x] References: Do all archival references that should have a DOI list one (e.g., papers, datasets, software)?

Review checklist for @rachelss

Conflict of interest

[x] As the reviewer I confirm that I have read the JOSE conflict of interest policy and that there are no conflicts of interest for me to review this work.

Code of Conduct

[x] I confirm that I read and will adhere to the JOSE code of conduct.

General checks

[x] Repository: Is the source for this learning module available at the repository url?
[x] License: Does the repository contain a plain-text LICENSE file with the contents of a standard license? (OSI-approved for code, Creative Commons for content)
[x] Version: Does the release version given match the repository release (v1.0.0)?
[x] Authorship: Has the submitting author (@wrightaprilm) made visible contributions to the module? Does the full list of authors seem appropriate and complete?

Documentation

[x] A statement of need: Do the authors clearly state the need for this module and who the target audience is?
[x] Installation instructions: Is there a clearly stated list of dependencies?
[x] Usage: Does the documentation explain how someone would adopt the module, and include examples of how to use it?
[x] Community guidelines: Are there clear guidelines for third parties wishing to 1) Contribute to the module 2) Report issues or problems with the module 3) Seek support

Pedagogy / Instructional design (Work-in-progress: reviewers, please comment!)

[x] Learning objectives: Does the module make the learning objectives plainly clear? (We don't require explicitly written learning objectives; only that they be evident from content and design.)
[x] Content scope and length: Is the content substantial for learning a given topic? Is the length of the module appropriate?
[x] Pedagogy: Does the module seem easy to follow? Does it observe guidance on cognitive load? (working memory limits of 7 +/- 2 chunks of information)
[x] Content quality: Is the writing of good quality, concise, engaging? Are the code components well crafted? Does the module seem complete?
[x] Instructional design: Is the instructional design deliberate and apparent? For example, exploit worked-example effects; effective multi-media use; low extraneous cognitive load.

JOSE paper

[x] Authors: Does the paper.md file include a list of authors with their affiliations?
[x] A statement of need: Does the paper clearly state the need for this module and who the target audience is?
[x] Description: Does the paper describe the learning materials and sequence?
[x] Does it describe how it has been used in the classroom or other settings, and how someone might adopt it?
[x] Could someone else teach with this module, given the right expertise?
[x] Does the paper tell the "story" of how the authors came to develop it, or what their expertise is?
[x] References: Do all archival references that should have a DOI list one (e.g., papers, datasets, software)?

whedon commented 5 years ago

PDF failed to compile for issue #35 with the following error:

% Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed

0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0 100 14 0 14 0 0 48 0 --:--:-- --:--:-- --:--:-- 48 pandoc-citeproc: reference Meisel2010 not found pandoc-citeproc: reference Meisel2010 not found pandoc-citeproc: reference sandvik not found pandoc-citeproc: reference rudolph1998 not found pandoc-citeproc: reference sandvik not found pandoc-citeproc: reference ohara1997 not found pandoc-citeproc: reference Meisel2010 not found pandoc-citeproc: reference Meisel2010 not found pandoc-citeproc: reference meir2007 not found /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/bibtex.rb:44:in make_citation': undefined methodhas_field?' for # (NoMethodError) from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/bibtex.rb:31:in block in generate_citations' from /app/vendor/bundle/ruby/2.4.0/gems/bibtex-ruby-4.4.7/lib/bibtex/bibliography.rb:150:ineach' from /app/vendor/bundle/ruby/2.4.0/gems/bibtex-ruby-4.4.7/lib/bibtex/bibliography.rb:150:in each' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/bibtex.rb:29:ingenerate_citations' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/processor.rb:214:in generate_crossref' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/processor.rb:91:incompile' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/bin/whedon:76:in compile' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/command.rb:27:inrun' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/invocation.rb:126:in invoke_command' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor.rb:387:indispatch' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/base.rb:466:in start' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/bin/whedon:113:in<top (required)>' from /app/vendor/bundle/ruby/2.4.0/bin/whedon:23:in load' from /app/vendor/bundle/ruby/2.4.0/bin/whedon:23:in

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wrightaprilm commented 5 years ago

Oops, forgot to push my updated .bib file. And because all my references in the vignettes and website build locally before pushing, this is the first step where that would be caught. I've pushed it now. Sorry all!

juanklopper commented 5 years ago

@wrightaprilm okay, no problem, let's try this again.

juanklopper commented 5 years ago

@whedon accept

whedon commented 5 years ago

Attempting dry run of processing paper acceptance...

whedon commented 5 years ago

PDF failed to compile for issue #35 with the following error:

% Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed

0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0 100 14 0 14 0 0 39 0 --:--:-- --:--:-- --:--:-- 39 pandoc-citeproc: reference sandvik not found pandoc-citeproc: reference sandvik not found /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/bibtex.rb:44:in make_citation': undefined methodhas_field?' for # (NoMethodError) from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/bibtex.rb:31:in block in generate_citations' from /app/vendor/bundle/ruby/2.4.0/gems/bibtex-ruby-4.4.7/lib/bibtex/bibliography.rb:150:ineach' from /app/vendor/bundle/ruby/2.4.0/gems/bibtex-ruby-4.4.7/lib/bibtex/bibliography.rb:150:in each' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/bibtex.rb:29:ingenerate_citations' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/processor.rb:214:in generate_crossref' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/processor.rb:91:incompile' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/bin/whedon:76:in compile' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/command.rb:27:inrun' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/invocation.rb:126:in invoke_command' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor.rb:387:indispatch' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/base.rb:466:in start' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/bin/whedon:113:in<top (required)>' from /app/vendor/bundle/ruby/2.4.0/bin/whedon:23:in load' from /app/vendor/bundle/ruby/2.4.0/bin/whedon:23:in

'

labarba commented 5 years ago

@whedon generate pdf

whedon commented 5 years ago

Attempting PDF compilation. Reticulating splines etc...

whedon commented 5 years ago

:point_right: Check article proof :page_facing_up: :point_left:

labarba commented 5 years ago

@whedon accept

whedon commented 5 years ago

Attempting dry run of processing paper acceptance...

whedon commented 5 years ago

PDF failed to compile for issue #35 with the following error:

% Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed

0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0 100 14 0 14 0 0 19 0 --:--:-- --:--:-- --:--:-- 19 /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/bibtex.rb:44:in make_citation': undefined methodhas_field?' for # (NoMethodError) from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/bibtex.rb:31:in block in generate_citations' from /app/vendor/bundle/ruby/2.4.0/gems/bibtex-ruby-4.4.7/lib/bibtex/bibliography.rb:150:ineach' from /app/vendor/bundle/ruby/2.4.0/gems/bibtex-ruby-4.4.7/lib/bibtex/bibliography.rb:150:in each' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/bibtex.rb:29:ingenerate_citations' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/processor.rb:214:in generate_crossref' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/processor.rb:91:incompile' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/bin/whedon:76:in compile' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/command.rb:27:inrun' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/invocation.rb:126:in invoke_command' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor.rb:387:indispatch' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/base.rb:466:in start' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/bin/whedon:113:in<top (required)>' from /app/vendor/bundle/ruby/2.4.0/bin/whedon:23:in load' from /app/vendor/bundle/ruby/2.4.0/bin/whedon:23:in

'

labarba commented 5 years ago

Hmm ... I think we ran into a funky bug. @arfon — What could be going on? @whedon accept fails, but @whedon generate pdf does compile the paper.

wrightaprilm commented 5 years ago

I think this is actually my issue. I use this bibtex on multiple multiple-author projects, and we include some string expansions for journals we cite from a bunch. I removed the translation block.

labarba commented 5 years ago

@whedon accept

whedon commented 5 years ago

Attempting dry run of processing paper acceptance...

whedon commented 5 years ago

PDF failed to compile for issue #35 with the following error:

% Total % Received % Xferd Average Speed Time Time Time Current Dload Upload Total Spent Left Speed

0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0 100 14 0 14 0 0 46 0 --:--:-- --:--:-- --:--:-- 46 /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/processor.rb:225:in ``': Argument list too long - cd tmp/35 && pandoc -V timestamp=20190116200213 -V doi_batch_id=858dbd49d7453083a43e92e3a1843090 -V formatted_doi=10.21105/jose.00035 -V archive_doi="https://doi.org/10.5281/zenodo.2541824" -V review_issue_url=https://github.com/openjournals/jose-reviews/issues/35 -V paper_url=http://www.theoj.org/openjournals/jose-papers/jose.00035/10.21105.jose.00035.pdf -V joss_resource_url=https://jose.theoj.org/papers/10.21105/jose.00035 -V journal_alias=jose -V journal_abbrev_title=JOSE -V journal_url=https://jose.theoj.org -V journal_name='Journal of Open Source Education' -V journal_issn=2577-3569 -V citations=' (Errno::E2BIG)

\textitKretzoiarctos gen. nov., the Oldest Member of the Giant Panda Clade, Abella, Juan and Alba, David M. and Robles, Josep M. and Valenciano, Alberto and Rotgers, Cheyenn and Carmona, Raül and Montoya, Plinio and Morales, Jorge, PLoS One, 2012, e48985, 17 Una nueva especie de \textitAgriarctos (Ailuropodinae, Ursidae, Carnivora) en la localidad de Nombrevilla 2 (Zaragoza, España), Abella, J and Montoya, P and Morales, J, Estudios Geológicos, 2011, 2, 187–191, 67 10.1371/journal.pcbi.1003537 The fossilized birth-death process for coherent calibration of divergence-time estimates, Heath, Tracy A and Huelsenbeck, John P and Stadler, Tanja, pnas, 2014, 29, E2957–E2966, 111, National Acad Sciences, 2015.05.31 PhyloBayes 3: a Bayesian software package for phylogenetic reconstruction and molecular dating, Lartillot, N. and Lepage, T. and Blanquart, S., bi, 2009, 17, 2286, 25, Oxford Univ Press, 2011.07.11 APE: analyses of phylogenetics and evolution in R language, Paradis, E. and Claude, J. and Strimmer, K., bi, 2004, 2, 289–290, 20, Oxford Univ Press, 2012.09.26 10.1093/bioinformatics/btu033 10.1111/j.2041-210X.2011.00169.x Modeling Character Change Heterogeneity in Phylogenetic Analyses of Morphology through the Use of Priors, Wright, April M. and Lloyd, Graeme T. and Hillis, David M., sysbio, 2016, 4, 602-611, 65 Confidence limits on phylogenies: an approach using the bootstrap, Felsenstein, J., evolution, 1985, 4, 783–791, 39, shhn001, 2008.11.25 Numerical taxonomy, Sneath, P.H.A. and Sokal, R.R., Springer, 1973, shhn001, 2009.02.23 APE: analyses of phylogenetics and evolution in R language, Paradis, E. and Claude, J. and Strimmer, K., bi, 2004, 2, 289–290, 20, Oxford Univ Press, 2012.09.26 10.1093/bioinformatics/btu033 10.1111/j.2041-210X.2011.00169.x \textitKretzoiarctos gen. nov., the Oldest Member of the Giant Panda Clade, Abella, Juan and Alba, David M. and Robles, Josep M. and Valenciano, Alberto and Rotgers, Cheyenn and Carmona, Raül and Montoya, Plinio and Morales, Jorge, PLoS One, 2012, e48985, 17 Una nueva especie de \textitAgriarctos (Ailuropodinae, Ursidae, Carnivora) en la localidad de Nombrevilla 2 (Zaragoza, España), Abella, J and Montoya, P and Morales, J, Estudios Geológicos, 2011, 2, 187–191, 67 10.1073/pnas.1116871109 On Small-Sample Confidence Intervals for Parameters in Discrete Distributions, Agresti, Alan and Min, Yongyi, Biometrics, 2001, 963–971, 57, The traditional definition of a confidence interval requires the coverage probability at any value of the parameter to be at least the nominal confidence level. In constructing such intervals for parameters in discrete distributions, less conservative behavior results from inverting a single two-sided test than inverting two separate one-sided tests of half the nominal level each. We illustrate for a variety of discrete problems, including interval estimation of a binomial parameter, the difference and the ratio of two binomial parameters for independent samples, and the odds ratio., Copyright � 2001 International Biometric Society, 0006341X, primary_article, Sep., 2001, shhn001, International Biometric Society, 2008.12.04 Mathematical foundations for signal processing, communications, and networking, Ahmadi, Aitzaz and Serpedini, Erchin and Qaraqell, Khalid Az, 13. Factor Graphs and Message Passing Algorithms, Erchin Serpedini, Thomas Chen and Rajan, Dinesh, CRC Press, 2012, hoehna, 2013.12.03 Inferring a Tree from Lowest Common Ancestors with an Application to the Optimization of Relational Expressions, Aho, AV and Sagiv, Y. and Szymanski, TG and Ullman, JD, SIAM Journal on Computing, 1981, 405, 10, shhn001, SIAM, 2008.09.17 Posterior bayes factors, Aitkin, Murray, Journal of the Royal Statistical Society. Series B (Methodological), 1991, 111–142, 53, hoehna, JSTOR, 2013.03.26 Information theory and an extension of the maximum likelihood principle, Akaike, Hirotogu, Selected Papers of Hirotugu Akaike, Springer, 1998, 199–213, hoehna, 2013.04.07 A new look at the statistical model identification, Akaike, Hirotugu, Automatic Control, IEEE Transactions on, 1974, 6, 716–723, 19, hoehna, Ieee, 2013.04.23 A critical branching process model for biodiversity, Aldous, D. and Popovic, L., Advances in applied probability, 2005, 4, 1094–1115, 37, hoehna, Applied Probability Trust, 2012.03.16 Stochastic models and descriptive statistics for phylogenetic trees, from Yule to today, Aldous, David J, Statistical Science, 2001, 23–34, hoehna, JSTOR, 2015.08.25 Nine exceptional radiations plus high turnover explain species diversity in jawed vertebrates, Alfaro, M.E. and Santini, F. and Brock, C. and Alamillo, H. and Dornburg, A. and Rabosky, D.L. and Carnevale, G. and Harmon, L.J., pnas, 2009, 32, 13410–13414, 106, hoehna, National Acad Sciences, 2012.11.22 The posterior and the prior in Bayesian phylogenetics, Alfaro, Michael E. and Holder, Mark T., arees, 2006, 1, 19-42, 37, http://www.annualreviews.org/doi/pdf/10.1146/annurev.ecolsys.37.091305.110021, hoehna, 2009.10.13 Comparative performance of Bayesian and AIC-based measures of phylogenetic model uncertainty, Alfaro, Michael E and Huelsenbeck, John P, sysbio, 2006, 1, 89–96, 55, hoehna, Oxford University Press, 2014.10.18 Bayes or Bootstrap? A Simulation Study Comparing the Performance of Bayesian Markov Chain Monte Carlo Sampling and Bootstrapping in Assessing Phylogenetic Confidence, Alfaro, Michael E. and Zoller, Stefan and Lutzoni, F., mbe, 2003, 2, 255-266, 20, Bayesian Markov chain Monte Carlo sampling has become increasingly popular in phylogenetics as a method for both estimating the maximum likelihood topology and for assessing nodal confidence. Despite the growing use of posterior probabilities, the relationship between the Bayesian measure of confidence and the most commonly used confidence measure in phylogenetics, the nonparametric bootstrap proportion, is poorly understood. We used computer simulation to investigate the behavior of three phylogenetic confidence methods: Bayesian posterior probabilities calculated via Markov chain Monte Carlo sampling (BMCMC-PP), maximum likelihood bootstrap proportion (ML-BP), and maximum parsimony bootstrap proportion (MP-BP). We simulated the evolution of DNA sequence on 17-taxon topologies under 18 evolutionary scenarios and examined the performance of these methods in assigning confidence to correct monophyletic and incorrect monophyletic groups, and we examined the effects of increasing character number on support value. BMCMC-PP and ML-BP were often strongly correlated with one another but could provide substantially different estimates of support on short internodes. In contrast, BMCMC-PP correlated poorly with MP-BP across most of the simulation conditions that we examined. For a given threshold value, more correct monophyletic groups were supported by BMCMC-PP than by either ML-BP or MP-BP. When threshold values were chosen that fixed the rate of accepting incorrect monophyletic relationship as true at 5%, all three methods recovered most of the correct relationships on the simulated topologies, although BMCMC-PP and ML-BP performed better than MP-BP. BMCMC-PP was usually a less biased predictor of phylogenetic accuracy than either bootstrapping method. BMCMC-PP provided high support values for correct topological bipartitions with fewer characters than was needed for nonparametric bootstrap., http://mbe.oxfordjournals.org/content/20/2/255.full.pdf+html, hoehna, 2011.09.15 Phylodynamics of H5N1 Highly Pathogenic Avian Influenza in Europe, 2005–2010: Potential for Molecular Surveillance of New Outbreaks, Alkhamis, Mohammad A and Moore, Brian R and Perez, Andrés M, Viruses, 2015, 6, 3310–3328, 7, hoehna, Multidisciplinary Digital Publishing Institute, 2015.08.13 Subtree Transfer Operations and Their Induced Metrics on Evolutionary Trees, Allen, B.L. and Steel, Mike, Annals of Combinatorics, 2001, 1, 1–15, 5, shhn001, Springer, 2008.12.01 Dynamics of origination and extinction in the marine fossil record, Alroy, John, pnas, 2008, Supplement 1, 11536–11542, 105, hoehna, National Acad Sciences, 2015.05.13 Cope’s rule and the dynamics of body mass evolution in North American fossil mammals, Alroy, John, Science, 1998, 5364, 731–734, 280, hoehna, American Association for the Advancement of Science, 2015.01.20 Non-monophyly and intricate morphological evolution within the avian family Cettiidae revealed by multilocus analysis of a taxonomically densely sampled dataset, Alström, P. and Höhna, S. and Gelang, M. and Ericson, P.G.P. and Olsson, U., bmcevobio, 2011, 1, 352, 11, hoehna, BioMed Central Ltd, 2011.07.12 Parallel metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference, Altekar, Gautam and Dwarkadas, Sandhya and Huelsenbeck, John P and Ronquist, Fredrik, bi, 2004, 3, 407–415, 20, hoehna, Oxford Univ Press, 2015.02.25 Adaptive evolution of non-coding DNA in Drosophila, Andolfatto, Peter, Nature, 2005, 7062, 1149–1152, 437, hoehna, Nature Publishing Group, 2013.08.11 New Miocene locality in Turkey with evidence on the origin of \textitRamapithecus and \textitSivapithecus, Andrews, P and Tobien, H, Nature, 1977, 5622, 699, 268 Accuracy and power of Bayes prediction of amino acid sites under positive selection, Anisimova, Maria and Bielawski, Joseph P and Yang, Ziheng, mbe, 2002, 6, 950–958, 19, hoehna, SMBE, 2013.08.10 Investigating protein-coding sequence evolution with probabilistic codon substitution models, Anisimova, Maria and Kosiol, Carolin, mbe, 2009, 2, 255–271, 26, hoehna, SMBE, 2013.08.10 Effect of recombination on the accuracy of the likelihood method for detecting positive selection at amino acid sites, Anisimova, Maria and Nielsen, Rasmus and Yang, Ziheng, genetics, 2003, 3, 1229–1236, 164, hoehna, Genetics Soc America, 2013.08.10 Mass extinction, gradual cooling, or rapid radiation? Reconstructing the spatiotemporal evolution of the ancient angiosperm genus Hedyosmum (Chloranthaceae) using empirical and simulated approaches, Antonelli, A. and Sanmartı́n, I., sysbio, 2011, 5, 596–615, 60, hoehna, Oxford University Press, 2012.08.01 Dating phylogenies with hybrid local molecular clocks, Aris-Brosou, Stéphane, pone, 2007, 9, e879, 2, hoehna, Public Library of Science, 2014.06.05 Bayesian models of episodic evolution support a late Precambrian explosive diversification of the Metazoa, Aris-Brosou, Stéphane and Yang, Ziheng, mbe, 2003, 12, 1947–1954, 20, hoehna, SMBE, 2013.03.26 Effects of models of rate evolution on estimation of divergence dates with special reference to the metazoan 18S ribosomal RNA phylogeny, Aris-Brosou, Stéphane and Yang, Ziheng, sysbio, 2002, 5, 703–714, 51, hoehna, Oxford University Press, 2014.01.16 Bayesian gene/species tree reconciliation and orthology analysis using MCMC, Arvestad, Lars and Berglund, Ann-Charlotte and Lagergren, Jens and Sennblad, Bengt, bi, 2003, suppl 1, i7–i15, 19, hoehna, Oxford Univ Press, 2015.05.19 BEAGLE: an application programming interface and high-performance computing library for statistical phylogenetics, Ayres, Daniel L and Darling, Aaron and Zwickl, Derrick J and Beerli, Peter and Holder, Mark T and Lewis, Paul O and Huelsenbeck, John P and Ronquist, Fredrik and Swofford, David L and Cummings, Michael P and Rambaut, Andrew and Suchard, Marc A, sysbio, 2012, 1, 170-173, 61, hoehna, Oxford University Press, 2014.11.29 Computational Grand Challenges in Assembling the Tree of Life: Problems and Solutions, Bader, D.A. and Roshan, U. and Stamatakis, A., ADVANCES IN COMPUTERS, 2006, 128, 68, shhn001, ACADEMIC PRESS, INC, 2008.11.06 Bayesian evolutionary model testing in the phylogenomics era: matching model complexity with computational efficiency, Baele, Guy and Lemey, Philippe, bi, 2013, 16, 1970-1979, 29, hoehna, Oxford University Press, 2015.03.16 Improving the Accuracy of Demographic and Molecular Clock Model Comparison while Accommodating Phylogenetic Uncertainty, Baele, G. and Lemey, P. and Bedford, T. and Rambaut, A. and Suchard, M.A. and Alekseyenko, A.V., mbe, 2012, 9, 2157–2167, 29, hoehna, SMBE, 2013.01.24 Make the most of your samples: Bayes factor estimators for high-dimensional models of sequence evolution, Baele, Guy and Lemey, Philippe and Vansteelandt, Stijn, BMC bioinformatics, 2013, 1, 85, 14, hoehna, BioMed Central Ltd, 2015.03.16 Accurate Model Selection of Relaxed Molecular Clocks in Bayesian Phylogenetics, Baele, G. and Li, W.L.S. and Drummond, A.J. and Suchard, M.A. and Lemey, P., mbe, 2013, 2, 239–243, 30, hoehna, SMBE, 2013.01.24 Chloroplast DNA evidence for a North American origin of the Hawaiian silversword alliance (Asteraceae), Baldwin, Bruce G and Kyhos, Donald W and Dvorak, Jan and Carr, Gerald D, Proceedings of the National Academy of Sciences, 1991, 5, 1840–1843, 88, National Acad Sciences Age and rate of diversification of the Hawaiian silversword alliance (Compositae), Baldwin, Bruce G and Sanderson, Michael J, Proceedings of the National Academy of Sciences, 1998, 16, 9402–9406, 95, National Acad Sciences Effects of Oligo-Miocene global climate changes on mammalian species richness in the northwestern quarter of the USA, Barnosky, A.D. and Carrasco, M.A., Evolutionary Ecology Research, 2002, 6, 811–841, 4, hoehna, 2013.01.11 Has the Earth’s sixth mass extinction already arrived?, Barnosky, A.D. and Matzke, N. and Tomiya, S. and Wogan, G.O.U. and Swartz, B. and Quental, T.B. and Marshall, C. and McGuire, J.L. and Lindsey, E.L. and Maguire, K.C. and others, Nature, 2011, 7336, 51–57, 471, hoehna, Nature Publishing Group, 2013.01.11 Late Miocene \textitIndarctos punjabiensis atticus (Carnivora, Ursidae) in Ukraine with survey of \textitIndarctos records from the former USSR, Baryshnikov, Gennady F, Russian J. Theriol, 2002, 2, 83–89, 1 Landscapes on Spaces of Trees, Bastert, Oliver and Rockmore, Dan and Stadler, Peter F. and Tinhofer, Gottfried, Applied Mathematics and Computation, 2002, 439–459, 131, September, 2, 439-459, 131 The MRP method, Baum, B.R. and Ragan, M.A., Kluwer Academic Pub, 2004, Phylogenetic Supertrees: Combining Information to Reveal the Tree of Life, shhn001, 17–34, 2008.09.17 10.1126/science.1117727 Combining Trees as a Way of Combining Data Sets for Phylogenetic Inference, and the Desirability of Combining Gene Trees, Baum, Bernard R., Taxon, 1992, 1, 3–10, 41, A procedure of combining trees obtained from data sets of different kinds, similar to Brooks’s technique but for a different purpose, with the aim of combining these data sets, is detailed along with examples used in five unrepeated combinations from a total of 15 published datasets. The procedure does not adjoin raw data sets, but instead combines the binary-coded factors of the trees, each tree from a different data set, together. This allows the combining of data that are only available as pair-wise distances with data obtained directly from characters of the organisms. It economizes the analysis of combined nucleotide sequence data which can be very large, and preserves information for each kind of data in the combination. The procedure allows for missing data as well, and can be regarded as a new consensus method – mathematical properties have yet to be investigated. The desirability of combining gene trees, obtained from molecular data, to enable the inference of species trees is discussed in light of using this procedure., Copyright � 1992 International Association for Plant Taxonomy (IAPT), 00400262, primary_article, Feb., 1992, shhn001, International Association for Plant Taxonomy (IAPT), 2008.09.16 The Bayesian revolution in genetics, Beaumont, Mark A and Rannala, Bruce, Nature Reviews Genetics, 2004, 4, 251–261, 5, hoehna, Nature Publishing Group, 2013.08.10 Approximate Bayesian computation in population genetics, Beaumont, M.A. and Zhang, W. and Balding, D.J., genetics, 2002, 4, 2025–2035, 162, hoehna, Genetics Soc America, 2012.09.25 Migrate version 3.0 - a maximum likelihood and Bayesian estimator of gene flow using the coalescent., Beerli, Peter, jul, 2008, shhn001, 2009.01.03, http://popgen.scs.edu/migrate.html, 7 10.1073/pnas.081068098 Maximum-Likelihood Estimation of Migration Rates and Effective Population Numbers in Two Populations Using a Coalescent Approach, Beerli, Peter and Felsenstein, Joseph, genetics, 1999, 2, 763-773, 152, A new method for the estimation of migration rates and effective population sizes is described. It uses a maximum-likelihood framework based on coalescence theory. The parameters are estimated by Metropolis-Hastings importance sampling. In a two-population model this method estimates four parameters: the effective population size and the immigration rate for each population relative to the mutation rate. Summarizing over loci can be done by assuming either that the mutation rate is the same for all loci or that the mutation rates are gamma distributed among loci but the same for all sites of a locus. The estimates are as good as or better than those from an optimized FST-based measure. The program is available on the World Wide Web at http://evolution.genetics.washington.edu/lamarc.html., http://www.genetics.org/cgi/reprint/152/2/763.pdf, shhn001, 2009.02.16 Searching for Convergence in Phylogenetic Markov Chain Monte Carlo, Beiko, R. and Keith, J. and Harlow, T. and Ragan, M., sysbio, 2006, 4, 553–565, 55, shhn001, Taylor and Francis Ltd, 2009.01.10 Spatial Statistics and Bayesian Computation, Besag, Julian and Green, Peter J., Journal of the Royal Statistical Society. Series B (Methodological), 1993, 25–37, 55, Markov chain Monte Carlo (MCMC) algorithms, such as the Gibbs sampler, have provided a Bayesian inference machine in image analysis and in other areas of spatial statistics for several years, founded on the pioneering ideas of Ulf Grenander. More recently, the observation that hyperparameters can be included as part of the updating schedule and the fact that almost any multivariate distribution is equivalently a Markov random field has opened the way to the use of MCMC in general Bayesian computation. In this paper, we trace the early development of MCMC in Bayesian inference, review some recent computational progress in statistical physics, based on the introduction of auxiliary variables, and discuss its current and future relevance in Bayesian applications. We briefly describe a simple MCMC implementation for the Bayesian analysis of agricultural field experiments, with which we have some practical experience., Copyright © 1993 Royal Statistical Society, 00359246, primary_article, 1993, shhn001, Blackwell Publishing for the Royal Statistical Society, 2008.04.27 Geometry of the Space of Phylogenetic Trees, Billera, Louis J. and Holmes, Susan P. and Vogtmann, Karen, Advances in Applied Mathematics, 2001, 733–767, 27, November, 4, 733-767, 27 Phylogenetic Supertrees: Combining Information to Reveal the Tree of Life, Bininda-Emonds, ORP, Kluwer Academic Pub, 2004, shhn001, 2008.09.16 The evolution of supertrees, Bininda-Emonds, O.R.P., tee, 2004, 6, 315–322, 19, shhn001, Elsevier, 2008.09.16 The delayed rise of present-day mammals, Bininda-Emonds, O.R.P. and Cardillo, M. and Jones, K.E. and MacPhee, R.D.E. and Beck, R.M.D. and Grenyer, R. and Price, S.A. and Vos, R.A. and Gittleman, J.L. and Purvis, A., Nature, 2007, 7135, 507–512, 446, hoehna, Nature Publishing Group, 2013.01.11 The Carnivora of the Hagerman local fauna (late Pliocene) of Southwestern Idaho, Bjork, Philip Reese, Transactions of the American Philosophical Society, 1970, 7, 3–54, 60 Class of multiple sequence alignment algorithm affects genomic analysis, Blackburne, Benjamin P and Whelan, Simon, mbe, 2013, 3, 642–653, 30, hoehna, SMBE, 2013.08.10 A Bayesian Compound Stochastic Process for Modeling Nonstationary and Nonhomogeneous Sequence Evolution, Blanquart, Samuel and Lartillot, Nicolas, mbe, 2006, 2058-2071, 23, Variations of nucleotidic composition affect phylogenetic inference conducted under stationary models of evolution. In particular, they may cause unrelated taxa sharing similar base composition to be grouped together in the resulting phylogeny. To address this problem, we developed a nonstationary and nonhomogeneous model accounting for compositional biases. Unlike previous nonstationary models, which are branchwise, that is, assume that base composition only changes at the nodes of the tree, in our model, the process of compositional drift is totally uncoupled from the speciation events. In addition, the total number of events of compositional drift distributed across the tree is directly inferred from the data. We implemented the method in a Bayesian framework, relying on Markov Chain Monte Carlo algorithms, and applied it to several nucleotidic data sets. In most cases, the stationarity assumption was rejected in favor of our nonstationary model. In addition, we show that our method is able to resolve a well-known artifact. By Bayes factor evaluation, we compared our model with 2 previously developed nonstationary models. We show that the coupling between speciations and compositional shifts inherent to branchwise models may lead to an overparameterization, resulting in a lesser fit. In some cases, this leads to incorrect conclusions, concerning the nature of the compositional biases. In contrast, our compound model more flexibly adapts its effective number of parameters to the data sets under investigation. Altogether, our results show that accounting for nonstationary sequence evolution may require more elaborate and more flexible models than those currently used., http://mbe.oxfordjournals.org/cgi/reprint/23/11/2058.pdf, shhn001, Hastings Ratio definition, 2007.09.28 THE METHOD OF PROBITS, Bliss, CI, Science, 1934, 2037, 38–39, 79, shhn001, Method for calculating the inverse cumulative distribution function, 2008.05.28 Detection of punctuated equilibrium from molecular phylogenies, Bokma, F, Journal of Evolutionary Biology, 2002, 6, 1048–1056, 15, Wiley Online Library Problems detecting density-dependent diversification on phylogenies, Bokma, F., procb, 2009, 1659, 993, 276, hoehna, The Royal Society, 2011.09.08 Bayesian estimation of speciation and extinction probabilities from (in) complete phylogenies, Bokma, F., evolution, 2008, 9, 2441–2445, 62, hoehna, Wiley Online Library, 2012.09.25 Bayesian model adequacy and choice in phylogenetics, Bollback, J.P., mbe, 2002, 7, 1171–1180, 19, hoehna, SMBE, 2012.09.25 Evolutionary inference via the Poisson Indel Process, Bouchard-Côté, Alexandre and Jordan, Michael I, pnas, 2013, 4, 1160–1166, 110, hoehna, National Acad Sciences, 2013.07.30 BEAST 2: a software platform for Bayesian evolutionary analysis, Bouckaert, Remco and Heled, Joseph and Kühnert, Denise and Vaughan, Tim and Wu, Chieh-Hsi and Xie, Dong and Suchard, Marc A and Rambaut, Andrew and Drummond, Alexei J, PLoS computational biology, 2014, 4, e1003537, 10, hoehna, Public Library of Science, 2015.03.03 Arbres de Steiner et reseaux dont varie l�emplagement de certains sommets, Bourque, M., Ph. D. diss., Universite de Montreal, Quebec, Canada, 1978, shhn001, Symmetric Difference, 2007.09.26 Parallel adaptations to high temperatures in the Archaean eon, Boussau, Bastien and Blanquart, Samuel and Necsulea, Anamaria and Lartillot, Nicolas and Gouy, Manolo, Nature, 2008, 7224, 942–945, 456, hoehna, Nature Publishing Group, 2014.12.01 A mixture model and a hidden markov model to simultaneously detect recombination breakpoints and reconstruct phylogenies, Boussau, Bastien and Guéguen, Laurent and Gouy, Manolo, Evolutionary bioinformatics online, 2009, 67, 5, hoehna, Libertas Academica, 2013.07.16 Genome-scale coestimation of species and gene trees, Boussau, Bastien and Szöllősi, Gergely J and Duret, Laurent and Gouy, Manolo and Tannier, Eric and Daubin, Vincent, Genome research, 2013, 2, 323–330, 23, hoehna, Cold Spring Harbor Lab, 2013.05.31 Partitioned Bayesian analyses, partition choice, and the phylogenetic relationships of scincid lizards, Brandley, Matthew C and Schmitz, Andreas and Reeder, Tod W, sysbio, 2005, 3, 373–390, 54, hoehna, Oxford University Press, 2015.01.20 Bayesian support is larger than bootstrap support in phylogenetic inference: a mathematical argument, Britton, T. and Svennblad, B. and Erixon, P. and Oxelman, B., Mathematical Medicine and Biology, 2007, 4, 401, 24, hoehna, IMA, 2011.09.14 Phylogenetic Inferences from Molecular Sequences: Review and Critique, Brocchieri, L., tpb, 2001, 1, 27–40, 59, shhn001, Elsevier, 2008.04.02 Testing for temporal variation in diversification rates when sampling is incomplete and nonrandom, Brock, C.D. and Harmon, L.J. and Alfaro, M.E., sysbio, 2011, 4, 410–419, 60, hoehna, Oxford University Press, 2012.07.27 Hennig’s Parasitological Method: A Proposed Solution, Brooks, Daniel R., Systematic Zoology, 1981, 3, 229–249, 30, A quantitative solution for Hennig’s parasitological method is presented. Cladograms summarizing natural relationships among parasite taxa are converted into host-group characters by means of additive binary coding. Unrooted Wagner analysis followed by most parsimonious rooting produces a maximum information-content, representation of natural host-parasite relationships. Because host-parasite relationships result either from random colonization or from co-speciation, host relationships well corroborated by a multi-parasite analysis correspond to.host phylogeny. Poorly corroborated, host relationships indicate an ambiguous parasite message alerting a worker to possible host transfers. Thus, such analyses point out co-speciation and random colonization components of host-parasite systems. Single or multiple parasite taxa may be used. A host phylogeny based on non-parasite characters is neither necessary nor sufficient for studying phylogenetic aspects of coevolution, although such may be helpful in testing ambiguous aspects. Once a host-group cladogram based on .parasites has been established, phylogenetic interpretations for each observed host-parasite relationship may be made according to a listed set of necessary and sufficient criteria. Finally, evaluation of two models of coevolution, a "vicariance" model and the "resource-tracking" model, indicates that the latter cannot be extrapolated successfully to explain congruent phylogenetic differentiation of hosts and parasites and that the former model represents the general pattern of natural relationships among hosts and parasites., Copyright � 1981 Society of Systematic Biologists, 00397989, primary_article, Sep., 1981, shhn001, Taylor & Francis, Ltd. for the Society of Systematic Biologists, Additive Binary Coding Scheme., 2008.09.17 10.1111/1467-9884.00117 General methods for monitoring convergence of iterative simulations, Brooks, S.P. and Gelman, A., Journal of Computational and Graphical Statistics, 1998, 4, 434–455, 7, 1061-8600, Hoehna, JSTOR, 2011.03.03 Convergence assessment techniques for Markov chain Monte Carlo, Brooks, S.P. and Roberts, G.O., Statistics and Computing, 1998, 4, 319–335, 8, hoehna, Springer, 2009.05.13 Assessing convergence of Markov chain Monte Carlo algorithms, Brooks, S.P. and Roberts, G.O., Statistics and Computing, 1998, 4, 319–335, 8, Hoehna, Citeseer, 2011.03.03 PuMA: Bayesian analysis of partitioned (and unpartitioned) model adequacy, Brown, J.M. and ElDabaje, R., bi, 2009, 4, 537–538, 25, hoehna, Oxford Univ Press, 2012.09.25 Predictive approaches to assessing the fit of evolutionary models, Brown, Jeremy M, sysbio, 2014, 3, 289–292, 63, hoehna, Oxford University Press, 2015.05.15 Detection of implausible phylogenetic inferences using posterior predictive assessment of model fit, Brown, Jeremy M, sysbio, 2014, 3, 334–348, 63, hoehna, Oxford University Press, 2015.05.15 When Trees Grow Too Long: Investigating the Causes of Highly Inaccurate Bayesian Branch-Length Estimates, Brown, Jeremy M and Hedtke, Shannon M and Lemmon, Alan R and Lemmon, Emily Moriarty, sysbio, 2010, 2, 145–161, 59, hoehna, Oxford University Press, 2016.07.31 The importance of data partitioning and the utility of Bayes factors in Bayesian phylogenetics, Brown, Jeremy M and Lemmon, Alan R, sysbio, 2007, 4, 643–655, 56, hoehna, Oxford University Press, 2015.01.20 The higher-level phylogeny of Archosauria (Tetrapoda: Diapsida), Brusatte, Stephen L and Benton, Michael J and Desojo, Julia B and Langer, Max C, Journal of Systematic Palaeontology, 2010, 1, 3–47, 8, hoehna, Taylor & Francis, 2013.05.08 The Splits in the Neighborhood of a Tree, Bryant, D., Annals of Combinatorics, 2004, 1, 1–11, 8, shhn001, Springer, 2009.01.23 Building Trees, Hunting for Trees, and Comparing Trees: Theory and Methods in Phylogenetic Analysis, Bryant, D., University of Canterbury, 1997, shhn001, 2008.09.04 Hunting for trees in binary character sets., Bryant, David, Journal of Computational Biology, 1996, 275-288, 3, shhn001, 2008.09.04 Inferring species trees directly from biallelic genetic markers: bypassing gene trees in a full coalescent analysis, Bryant, David and Bouckaert, Remco and Felsenstein, Joseph and Rosenberg, Noah A and RoyChoudhury, Arindam, Molecular biology and evolution, 2012, 8, 1917–1932, 29, hoehna, SMBE, 2014.10.19 An evaluation of new parsimony-based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae, Buerki, Sven and Forest, Félix and Alvarez, Nadir and Nylander, Johan AA and Arrigo, Nils and Sanmartı́n, Isabel, Journal of Biogeography, 2011, 3, 531–550, 38, Wiley Online Library Partitioning and combining data in phylogenetic analysis, Bull, JJ and Huelsenbeck, John P and Cunningham, Clifford W and Swofford, David L and Waddell, Peter J, sysbio, 1993, 3, 384–397, 42, hoehna, Oxford University Press, 2015.02.25 Multimodel inference understanding AIC and BIC in model selection, Burnham, Kenneth P and Anderson, David R, Sociological methods & research, 2004, 2, 261–304, 33, hoehna, Sage Publications, 2013.04.19 Natural selection on protein-coding genes in the human genome, Bustamante, Carlos D and Fledel-Alon, Adi and Williamson, Scott and Nielsen, Rasmus and Hubisz, Melissa Todd and Glanowski, Stephen and Tanenbaum, David M and White, Thomas J and Sninsky, John J and Hernandez, Ryan D and Civello, Daniel and Adams, Mark D and Cargill, Michele and Clark, Andrew G., Nature, 2005, 7062, 1153–1157, 437, hoehna, Nature Publishing Group, 2013.08.10 A Method for Deducing Branching Sequences in Phylogeny, Camin, Joseph H. and Sokal, Robert R., evolution, 1965, sep, 3, 311–326, 19, A method is described for reconstructing presumed cladistic evolutionary sequences of recent organisms and its implications are discussed. Characters of the organisms to be studied are presented in a data matrix of the type employed in numerical taxonomy with the character states arrayed according to a presumed evolutionary sequence. The reconstruction proceeds on the hypothesis that the minimum number of evolutionary steps yields the correct cladogram. The method has been programmed for computer processing., Copyright 1965 Society for the Study of Evolution, 0014-3820, Full Length Article, 196509, Sep., 1965, shhn001, Society for the Study of Evolution, 2008.04.02, 9 Studies on Madinae: anatomy, cytology, and evolutionary relationships, Carlquist, Sherwin, Aliso, 1959, 2, 171–236, 4 Problems and solutions for estimating indel rates and length distributions, Cartwright, Reed A, mbe, 2009, 2, 473–480, 26, hoehna, SMBE, 2013.08.01 Phylogenetic Analysis: Models and Estimation Procedures, Cavalli-Sforza, L. L. and Edwards, A. W. F., evolution, 1967, 3, 550–570, 21, An attempt has been made to establish a procedure for estimating the course taken by evolution. The model used is that of a branching random walk, which is strictly valid only when the causes of divergence between populations are random genetic drift and variable selection. With suitable transformations of the data, evolution can then be considered as a branching Brownian-motion process. To keep the model as simple as possible it was supposed that no population becomes extinct and that each population splits, at a random time, into two daughter populations each identical to its parent. The problem was to estimate the form and dimensions of the most probable tree uniting the presently living populations. The ideal method of estimation, maximum likelihood, proved difficult and had to be replaced in part by alternative procedures. In addition to describing the available procedures in detail, a simple example is worked out fully, and the logical content and limitations of the methods are considered in depth., Copyright © 1967 Society for the Study of Evolution, 00143820, primary_article, Sep., 1967, shhn001, Society for the Study of Evolution, Discussion about the problem of how many rooted trees there are., 2008.04.25 SymmeTREE: whole-tree analysis of differential diversification rates, Chan, Kai MA and Moore, Brian R, bi, 2005, 8, 1709–1710, 21, hoehna, Oxford Univ Press, 2013.12.14 Whole-tree methods for detecting differential diversification rates, Chan, Kai MA and Moore, Brian R, Systematic Biology, 2002, 6, 855–865, 51, hoehna, Oxford University Press, 2015.08.13 Accounting for mode of speciation increases power and realism of tests of phylogenetic asymmetry, Chan, Kai MA and Moore, Brian R, an, 1999, 3, 332–346, 153, hoehna, JSTOR, 2015.03.04 Estimating the phylogeny and divergence times of primates using a supermatrix approach, Chatterjee, Helen J and Ho, Simon YW and Barnes, Ian and Groves, Colin, BMC Evolutionary Biology, 2009, 1, 259, 9, hoehna, BioMed Central Ltd, 2015.08.07 Monte Carlo methods in Bayesian computation, Chen, M.H. and Shao, Q.M. and Ibrahim, J.G., Springer, 2001, 0387989358, Hoehna, 2011.03.03 Vernon Kellogg, host-switching, and cospeciation: Rescuing straggled ideas, Choudhury, Anindo and Moore, Brian R and Marques, Fernando LP, Journal of Parasitology, 2002, 5, 1045–1048, 88, hoehna, 2015.08.13 Molecular dating, evolutionary rates, and the age of the grasses, Christin, Pascal-Antoine and Spriggs, Elizabeth and Osborne, Colin P and Strömberg, Caroline AE and Salamin, Nicolas and Edwards, Erika J, Systematic biology, 2014, 2, 153–165, 63, hoehna, Oxford University Press, 2015.09.08 \textitArctodus simus from the Alaskan Arctic slope, Churcher, CS and Morgan, AV and Carter, LD, Canadian Journal of Earth Sciences, 1993, 5, 1007–1013, 30 Evolution of genes and genomes on the Drosophila phylogeny, Clark, Andrew G and Eisen, Michael B and Smith, Douglas R and Bergman, Casey M and Oliver, Brian and Markow, Therese A and Kaufman, Thomas C and Kellis, Manolis and Gelbart, William and Iyer, Venky N and others, Nature, 2007, 7167, 203–218, 450, hoehna, Nature Publishing Group, 2013.08.12 10.1109/ICASSP.1999.757596 Arctoid Genetic Characters as Related to the Genus \emphParictis, Clark, John and Guensburg, Thomas Edgar, Field Museum of Natural History, 1972, Chicago, Ill., 1150 10.1093/biomet/26.4.404 Finishing the euchromatic sequence of the human genome, Collins, FS and Lander, ES and Rogers, J and Waterston, RH and Conso, IHGS, Nature, 2004, 7011, 931–945, 431, hoehna, 2013.08.11 Macroevolutionary perspectives to environmental change, Condamine, Fabien L and Rolland, Jonathan and Morlon, Hélène, el, 2013, hoehna, Wiley Online Library, 2013.04.19 An efficient algorithm for supertrees, Constantinescu, M. and Sankoff, D., Journal of Classification, 1995, 1, 101–112, 12, shhn001, Springer, 2008.09.17 Possible biases induced by MCMC convergence diagnostics, Cowles, M.K. and Roberts, G.O. and Rosenthal, J.S., Journal of Statistical Computation and Simulation, 1999, 1, 87, 64, hoehna, Citeseer, 2011.07.19 A simulation approach to convergence rates for Markov chain Monte Carlo algorithms, Cowles, M.K. and Rosenthal, J.S., Statistics and Computing, 1998, 2, 115–124, 8, hoehna, Springer, 2009.05.13 Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review, Cowles, Mary Kathryn and Carlin, Bradley P., jasa, 1996, 883–904, 91, A critical issue for users of Markov chain Monte Carlo (MCMC) methods in applications is how to determine when it is safe to stop sampling and use the samples to estimate characteristics of the distribution of interest. Research into methods of computing theoretical convergence bounds holds promise for the future but to date has yielded relatively little of practical use in applied work. Consequently, most MCMC users address the convergence problem by applying diagnostic tools to the output produced by running their samplers. After giving a brief overview of the area, we provide an expository review of 13 convergence diagnostics, describing the theoretical basis and practical implementation of each. We then compare their performance in two simple models and conclude that all of the methods can fail to detect the sorts of convergence failure that they were designed to identify. We thus recommend a combination of strategies aimed at evaluating and accelerating MCMC sampler convergence, including applying diagnostic procedures to a small number of parallel chains, monitoring autocorrelations and cross-correlations, and modifying parametrizations or sampling algorithms appropriately. We emphasize, however, that it is not possible to say with certainty that a finite sample from an MCMC algorithm is representative of an underlying stationary distribution., Copyright © 1996 American Statistical Association, 01621459, primary_article, Jun., 1996, American Statistical Association Explosive radiation or cryptic mass extinction? Interpreting signatures in molecular phylogenies, Crisp, Michael D and Cook, Lyn G, Evolution, 2009, 9, 2257–2265, 63, hoehna, Wiley Online Library, 2015.09.28 10.1080/10635150390218213 Slowdowns in diversification rates from real phylogenies may not be real, Cusimano, N. and Renner, S.S., sysbio, 2010, 4, 458, 59, hoehna, Oxford University Press, 2011.09.08 A new method for handling missing species in diversification analysis applicable to randomly or nonrandomly sampled phylogenies, Cusimano, Natalie and Stadler, Tanja and Renner, Susanne Sc, sysbio, 2012, 5, 785–792, 61, hoehna, Oxford University Press, 2012.07.27 On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life, Darwin, Charles, Murray, 1859, hoehna, 2013.10.12 On computing the nearest neighbor interchange distance, DasGupta, B. and He, X. and Jiang, T. and Li, M. and Tromp, J. and Zhang, L., 2000, 125–143, 55, Proc. DIMACS Workshop on Discrete Problems with Medical Applications, shhn001, 2009.01.23 Methods of numerical integration Computer science and applied mathematics, Davis, P.J. and Rabinowitz, P., Academic Press, 1984, shhn001, 2008.09.09 The origins of species richness in the Hymenoptera: insights from a family-level supertree, Davis, Robert and Baldauf, Sandra and Mayhew, Peter, bmcevobio, 2010, 1, 109, 10, hoehna, BioMed Central Ltd, 2013.05.08 Optimal algorithms for comparing trees with labeled leaves, Day, W.H.E., Journal of Classification, 1985, 1, 7–28, 2, shhn001, Springer, 2009.01.23 A database of vertebrate longevity records and their relation to other life-history traits, De Magalhaes, JP and Costa, J, Journal of evolutionary biology, 2009, 8, 1770–1774, 22, hoehna, Wiley Online Library, 2015.01.20 Gene tree discordance, phylogenetic inference and the multispecies coalescent, Degnan, James H and Rosenberg, Noah A, tee, 2009, 6, 332–340, 24, hoehna, Elsevier, 2013.04.17 The probability distribution of ranked gene trees on a species tree, Degnan, James H and Rosenberg, Noah A and Stadler, Tanja, Mathematical biosciences, 2012, 1, 45–55, 235, hoehna, Elsevier, 2013.06.11 Gene tree distributions under the coalescent process, Degnan, James H and Salter, Laura A, evolution, 2005, 1, 24–37, 59, hoehna, Wiley Online Library, 2013.06.11 Maximum likelihood from incomplete data via the EM algorithm, Dempster, A.P. and Laird, N.M. and Rubin, D.B. and others, Journal of the Royal Statistical Society. Series B (Methodological), 1977, 1, 1–38, 39, hoehna, Royal Statistical Society, 2010.10.27 devtools: Tools to Make Developing R Packages Easier, Wickham, Hadley and Hester, Jim and Chang, Winston, 2018, R package version 1.13.6, https://CRAN.R-project.org/package=devtools Toward an integrative historical biogeography, Donoghue, Michael J and Moore, Brian R, Integrative and Comparative Biology, 2003, 2, 261–270, 43, hoehna, Soc Integ Comp Biol, 2015.03.04 Rocks and clocks: calibrating the Tree of Life using fossils and molecules, Donoghue, Philip CJ and Benton, Michael J, Trends in Ecology & Evolution, 2007, 8, 424–431, 22, hoehna, Elsevier, 2015.08.07 Comparison of Bayesian and Maximum Likelihood Bootstrap Measures of Phylogenetic Reliability, Douady, C.J. and Delsuc, F. and Boucher, Y. and Doolittle, W.F. and Douzery, E.J.P., mbe, 2003, 2, 248–254, 20, shhn001, SMBE, 2009.02.23 Relaxed Phylogenetics and Dating with Confidence, Drummond, AJ and Ho, SYW and Phillips, MJ and Rambaut, A., pbio, 2006, 5, e88, 4, shhn001, 2008.12.01 Measurably evolving populations, Drummond, A.J. and Pybus, O.G. and Rambaut, A. and Forsberg, R. and Rodrigo, A.G., tee, 2003, 9, 481–488, 18, hoehna, Elsevier Ltd, Review for serially sampled data. Coalescence Theory, Population Size, Divergence Times, 2009.07.21 BEAST: Bayesian evolutionary analysis sampling trees, Drummond, A. and Rambaut, A., bmcevobio, 2007, 214, 7, shhn001, 2008.03.25 Bayesian random local clocks, or one rate to rule them all, Drummond, A.J. and Suchard, M.A., bmcbio, 2010, 1, 114, 8, 1741-7007, Hoehna, BioMed Central Ltd, 2010.11.25 Bayesian phylogenetics with BEAUti and the BEAST 1.7, Drummond, A.J. and Suchard, M.A. and Xie, D. and Rambaut, A., mbe, 2012, 1969-1973, 29, hoehna, SMBE, 2012.07.25 Estimating Mutation Parameters, Population History and Genealogy Simultaneously From Temporally Spaced Sequence Data, Drummond, Alexei J. and Nicholls, Geoff K. and Rodrigo, Allen G. and Solomon, Wiremu, genetics, 2002, 3, 1307-1320, 161, Molecular sequences obtained at different sampling times from populations of rapidly evolving pathogens and from ancient subfossil and fossil sources are increasingly available with modern sequencing technology. Here, we present a Bayesian statistical inference approach to the joint estimation of mutation rate and population size that incorporates the uncertainty in the genealogy of such temporally spaced sequences by using Markov chain Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the time structure of the ancestral tree. We recover information about the unknown true ancestral coalescent tree, population size, and the overall mutation rate from temporally spaced data, that is, from nucleotide sequences gathered at different times, from different individuals, in an evolving haploid population. We briefly discuss the methodological implications and show what can be inferred, in various practically relevant states of prior knowledge. We develop extensions for exponentially growing population size and joint estimation of substitution model parameters. We illustrate some of the important features of this approach on a genealogy of HIV-1 envelope (env) partial sequences., http://www.genetics.org/cgi/reprint/161/3/1307.pdf, shhn001, 2008.04.26 Fully Bayesian tests of neutrality using genealogical summary statistics, Drummond, Alexei J and Suchard, Marc A, BMC genetics, 2008, 1, 68, 9, hoehna, BioMed Central Ltd, 2015.05.14 Reconstruction of large phylogenetic trees: A parallel approach, Du, Z. and Lin, F. and Roshan, U.W., Computational Biology and Chemistry, 2005, 4, 273–280, 29, shhn001, Elsevier, 2008.11.06 Evaluating the adequacy of molecular clock models using posterior predictive simulations, Duchêne, David A and Duchêne, Sebastian and Holmes, Edward C and Ho, Simon YW, Molecular biology and evolution, 2015, msv154, hoehna, SMBE, 2015.09.08 Mammalian genome evolution is governed by multiple pacemakers, Duchêne, Sebastián and Ho, Simon YW, bi, 2015, btv121, hoehna, Oxford Univ Press, 2015.10.22 Using multiple relaxed-clock models to estimate evolutionary timescales from DNA sequence data, Duchêne, Sebastián and Ho, Simon YW, mpe, 2014, 65–70, 77, hoehna, Elsevier, 2015.10.22 The impact of calibration and clock-model choice on molecular estimates of divergence times, Duchêne, Sebastián and Lanfear, Robert and Ho, Simon YW, mpe, 2014, 277–289, 78, hoehna, Elsevier, 2015.09.08 Non-homogeneous models of sequence evolution in the Bio++ suite of libraries and programs, Dutheil, Julien and Boussau, Bastien, bmcevobio, 2008, 1, 255, 8, hoehna, BioMed Central Ltd, 2013.07.16 Estimation of the branch points of a branching diffusion process, Edwards, Anthony WF, Journal of the Royal Statistical Society. Series B (Methodological), 1970, 155–174, hoehna, JSTOR, 2013.09.10 Is a new and general theory of molecular systematics emerging?, Edwards, Scott V, evolution, 2009, 1, 1–19, 63, hoehna, Wiley Online Library, 2013.04.17 High-resolution species trees without concatenation, Edwards, Scott V and Liu, Liang and Pearl, Dennis K, pnas, 2007, 14, 5936–5941, 104, hoehna, National Acad Sciences, 2013.04.17 10.1016/j.jbi.2005.11.007 Phylogenetic analysis and gene functional predictions: phylogenomics in action, Eisen, Jonathan A and Wu, Martin, tpb, 2002, 4, 481–487, 61, hoehna, Elsevier, 2013.12.15 Comparison of methodologies to assess the convergence of Markov chain Monte Carlo methods, El Adlouni, S. and Favre, A.C. and Bobée, B., Computational Statistics & Data Analysis, 2006, 10, 2685–2701, 50, 0167-9473, Hoehna, Elsevier, 2010.12.12 Reliability of Bayesian posterior probabilities and bootstrap frequencies in phylogenetics, Erixon, P. and Svennblad, B. and Britton, T. and Oxelman, B., sysbio, 2003, 5, 665, 52, hoehna, 2009.10.13 Macroevolution: Dynamics of Diversity, Erwin, D.H., Current Biology, 2011, 24, R1000–R1001, 21, hoehna, Elsevier, 2012.03.15 Estimating speciation and extinction rates from diversity data and the fossil record, Etienne, R.S. and Apol, M.E.F., evolution, 2009, 1, 244–255, 63, hoehna, Wiley Online Library, 2011.09.08 A Conceptual and Statistical Framework for Adaptive Radiations with a Key Role for Diversity Dependence, Etienne, R.S. and Haegeman, B., an, 2012, 4, 75–89, 180, hoehna, JSTOR, 2013.02.05 Diversity-dependence brings molecular phylogenies closer to agreement with the fossil record, Etienne, R.S. and Haegeman, B. and Stadler, T. and Aze, T. and Pearson, P.N. and Purvis, A. and Phillimore, A.B., procb, 2012, 1732, 1300–1309, 279, hoehna, The Royal Society, 2012.03.15 Prolonging the past counteracts the pull of the present: protracted speciation can explain observed slowdowns in diversification, Etienne, R.S. and Rosindell, J., sysbio, 2012, 2, 204–213, 61, hoehna, Oxford University Press, 2012.03.15 ESTIMATING THE DURATION OF SPECIATION FROM PHYLOGENIES, Etienne, Rampal S and Morlon, Héène and Lambert, Amaury, evolution, 2014, hoehna, Wiley Online Library, 2014.07.31 Confronting different models of community structure to species-abundance data: a Bayesian model comparison, Etienne, Rampal S and Olff, Han, el, 2005, 5, 493–504, 8, hoehna, Wiley Online Library, 2013.03.26 A novel genealogical approach to neutral biodiversity theory, Etienne, Rampal S and Olff, Han, el, 2004, 3, 170–175, 7, hoehna, Wiley Online Library, 2013.03.26 Choosing among Partition Models in Bayesian Phylogenetics, Fan, Yu and Wu, Rui and Chen, Ming-Hui and Kuo, Lynn and Lewis, Paul O, mbe, 2011, 1, 523–532, 28, hoehna, SMBE, 2015.01.20 Methods for Computing Wagner Trees, Farris, J.S., Systematic Zoology, 1970, 1, 83–92, 19, shhn001, JSTOR, 2008.04.02 PARSIMONY JACKKNIFING OUTPERFORMS NEIGHBOR-JOINING, Farris, J.S. and Albert, V.A. and Kallersjo, M. and Lipscomb, D. and Kluge, A.G., Cladistics, 1996, 2, 99–124, 12, shhn001, Blackwell Synergy, 2008.12.03 A Numerical Approach to Phylogenetic Systematics, Farris, James S. and Kluge, Arnold G. and Eckardt, Michael J., Systematic Zoology, 1970, 2, 172–189, 19, Principles abstracted from Hennig (1966) are used as axioms to form a quantitative analog of phylogenetic systematics. A close connection is demonstrated between phylogenetics and most parsimonious trees. The compatibility of some existing clustering methods with the principles is discussed. and a new clustering technique, the Weighted Invariant Step Strategy (WISS) is described. Generalization of the axioms to the case where direction of evolution is not assumed is examined, and it is shown that the Wagner Method for estimating evolutionary trees is consistent with the generalized phylogenetic axioms., Copyright � 1970 Society of Systematic Biologists, 00397989, primary_article, Jun., 1970, shhn001, Taylor & Francis, Ltd. for the Society of Systematic Biologists, Additive Binary Coding Scheme., 2008.09.16 PHYLIP (phylogeny inference package) version 3.6, Felsenstein, J., 2005, Distributed by the author. Department of Genome Sciences, University of Washington, Seattle, hoehna, 2009.11.17 Inferring Phylogenies, Felsenstein, Joseph, Sunderland, Massachusetts: Sinauer Associates, 2004, hoehna, 2012.09.25 Phylogenies from Restriction Sites: A Maximum-Likelihood Approach, Felsenstein, Joseph, Evolution, 1992, 1, 159-173, 46, 00143820, 15585646, [Society for the Study of Evolution, Wiley], http://www.jstor.org/stable/2409811 10.1146/annurev.ge.22.120188.002513 Confidence limits on phylogenies: an approach using the bootstrap, Felsenstein, J., evolution, 1985, 4, 783–791, 39, shhn001, 2008.11.25 Phylogenies and the comparative method, Felsenstein, Joseph, an, 1985, 1–15, hoehna, JSTOR, 2015.01.20 Distance Methods for Inferring Phylogenies: A Justification, Felsenstein, Joseph, evolution, 1984, 1, 16–24, 38, The logic of inferring phylogenies from measures of the phenotypic distance between species is examined, and a statistical model constructed. Criticisms which have been levelled by Farris (1981) against methods of inferring phylogenies from distances are dependent on one particular interpretation of the entity being inferred. If we take the branch lengths on the tree to be expected distances rather than path lengths, the major criticisms of these methods lose their force. Under the expected distance view, there is no reason to abandon distance measures solely because they fail to satisfy the triangle inequality. The expected distance interpretation fits naturally into a statistical inference framework for inferring phylogenies. This in turn provides justification for some of the most widely-used criteria of goodness of fit between a tree and the observed distances. However, the statistical framework does emphasize the weakness of distance methods if the assumptions of additivity of distances among the tree and of independence of the measurement errors of the distances are not met. The possible failure of additivity and of independence seem to be the most serious problems with using distance methods. These assumptions are dubious for many kinds of data often analyzed by distance methods. The assumption of a molecular clock affects the details of the computations, but can be fit into the statistical framework without difficulty. Given the validity of the additivity and independence assumptions, a statistical test of the clock could be performed., Copyright � 1984 Society for the Study of Evolution, 00143820, primary_article, Jan., 1984, shhn001, Society for the Study of Evolution, 2008.12.02 Parsimony in systematics: biological and statistical issues, Felsenstein, J., Annual Review of Ecology and Systematics, 1983, 313–333, 14, hoehna, JSTOR, 2011.09.15 Evolutionary Trees from DNA Sequences: a Maximum Likelihood Approach, Felsenstein, J., jme, 1981, 6, 368–376, 17, shhn001, Springer, 2008.04.04 The Number of Evolutionary Trees, Felsenstein, Joseph, Systematic Zoology, 1978, 1, 27–33, 27, A simple method of counting the number of possible evolutionary trees is presented. The trees are assumed to be rooted, with labelled tips but unlabelled root and unlabelled interior nodes. The method allows multifurcations as well as bifurcations. It makes use of a simple recurrence relation for T(n,m), the number of trees with n labelled tips and m unlabelled interior nodes. A table of the total number of trees is presented up to n = 22. There are 282,137,824 different trees having 10 tip species, and over 8.87 x 10<sup>23</sup> different trees having 20 tip species. The method is extended to count trees some of whose interior nodes may be labelled. The principal uses of these numbers will be to double-check algorithms and notation systems, and to frighten taxonomists., Copyright ? 1978 Society of Systematic Biologists, 00397989, primary_article, Mar., 1978, hoehna, Taylor & Francis, Ltd. for the Society of Systematic Biologists, 2009.08.05 Maximum Likelihood and Minimum-Steps Methods for Estimating Evolutionary Trees from Data on Discrete Characters, Felsenstein, J., Systematic Zoology, 1973, 3, 240–249, 22, shhn001, JSTOR, 2008.04.02 Maximum-likelihood estimation of evolutionary trees from continuous characters., Felsenstein, J., Am J Hum Genet, 1973, 5, 471–92, 25, shhn001, 2008.04.02 Statistical Inference and the Estimation of Phylogenies., Felsenstein, J., University of Chicago, Dept. of Zoology, 1968, shhn001, 2008.11.07 Construction of Phylogenetic Trees, Fitch, W.M. and Margoliash, E., Science, 1967, 3760, 279–284, 155, shhn001, 2009.02.23 Progressive sequence alignment as a prerequisitetto correct phylogenetic trees, Feng, Da-Fei and Doolittle, Russell F, Journal of molecular evolution, 25, 4, 351–360, 1987, Springer 10.2307/2412452 Toward Defining the Course of Evolution: Minimum Change for a Specific Tree Topology, Fitch, Walter M., Systematic Zoology, 1971, dec, 4, 406–416, 20, A method is presented that is asserted to provide all hypothetical ancestral character states that are consistent with describing the descent of the present-day character states in a minimum number of changes of state using a predetermined phylogenetic relationship among the taxa represented. The character states used as examples are the four messenger RNA nucleotides encoding the amino acid sequences of proteins, but the method is general., Copyright 1971 Society of Systematic Biologists, 0039-7989, Full Length Article, 197112, Dec., 1971, Evolution, Parsimonious Trees, shhn001, Society of Systematic Biologists, 2008.04.02, 12 Estimating trait-dependent speciation and extinction rates from incompletely resolved phylogenies, FitzJohn, R.G. and Maddison, W.P. and Otto, S.P., sysbio, 2009, 6, 595–611, 58, Hoehna, 2010.11.06 Diversitree: Comparative Phylogenetic Analyses of Diversification in R, FitzJohn, Richard G, mee, 2012, 6, 1084–1092, 3, hoehna, Wiley Online Library, 2014.06.16 Quantitative Traits and Diversification, FitzJohn, Richard G, sysbio, 2010, 6, 619-633, 59, hoehna, Oxford University Press, 2015.02.25 Diversification of land plants: insights from a family-level phylogenetic analysis, Fiz-Palacios, Omar and Schneider, Harald and Heinrichs, Jochen and Savolainen, Vincent, bmcevobio, 2011, 1, 341, 11, hoehna, BioMed Central Ltd, 2013.05.08 Markov chain Monte Carlo: Can we trust the third significant figure, Flegal, J.M. and Haran, M. and Jones, G.L., Statistical Science, 2008, 2, 250–260, 23, Hoehna, Institute of Mathematical Statistics, 2011.03.03 Simultaneous Statistical Multiple Alignment and Phylogeny Reconstruction, Fleissner, R. and Metzler, D. and von Haeseler, A., sysbio, 2005, 4, 548–561, 54, shhn001, Taylor & Francis, 2008.12.01 The effect of insertions, deletions, and alignment errors on the branch-site test of positive selection, Fletcher, William and Yang, Ziheng, mbe, 2010, 10, 2257–2267, 27, hoehna, SMBE, 2013.08.10 The phylogenetic likelihood library, Flouri, T and Izquierdo-Carrasco, F and Darriba, D and Aberer, AJ and Nguyen, L-T and Minh, BQ and Von Haeseler, A and Stamatakis, A, sysbio, 2015, 2, 356-362, 64, hoehna, Oxford University Press, 2015.02.25 On the probability of ancestors in the fossil record, Foote, Michael, Paleobiology, 1996, 141–151, 22 A method for investigating relative timing information on phylogenetic trees, Ford, Daniel and Gernhard, Tanja and Matsen, Erick, sysbio, 2009, 2, 167, 58, Hoehna, 2010.11.03 The viterbi algorithm, Forney Jr, G David, Proceedings of the IEEE, 1973, 3, 268–278, 61, hoehna, IEEE, 2013.12.03 P4, A python package for phylogenetics, Foster, PG, 2003, shhn001, Distributed by the author, 2008.12.01 Complete primate skeleton from the middle Eocene of Messel in Germany: morphology and paleobiology, Franzen, Jens L and Gingerich, Philip D and Habersetzer, Jörg and Hurum, Jørn H and von Koenigswald, Wighart and Smith, B Holly, pone, 2009, 5, e5723, 4, hoehna, Public Library of Science, 2015.07.30 Cladogenetic and anagenetic models of chromosome number evolution: a Bayesian model averaging approach, Freyman, William A and Höhna, Sebastian, Systematic Biology, 2017, syx065 Inferring cellular networks using probabilistic graphical models, Friedman, Nir, Science, 2004, 5659, 799–805, 303, hoehna, American Association for the Advancement of Science, 2013.05.20 Learning Bayesian networks with local structure, Friedman, Nir and Goldszmidt, Moises, Learning in graphical models, Springer, 1998, 421–459, hoehna, 2013.05.20 A structural EM algorithm for phylogenetic inference, Friedman, Nir and Ninio, Matan and Pe’er, Itsik and Pupko, Tal, Journal of Computational Biology, 2002, 2, 331–353, 9, hoehna, Mary Ann Liebert, Inc., 2013.05.20 Improving power posterior estimation of statistical evidence, Friel, Nial and Hurn, Merrilee and Wyse, Jason, Statistics and Computing, 2014, 5, 709–723, 24, hoehna, Springer, 2015.03.16 Marginal likelihood estimation via power posteriors, Friel, Nial and Pettitt, Anthony N, Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2008, 3, 589–607, 70, hoehna, Wiley Online Library, 2015.03.16 On the role of species in anagenesis, Futuyma, D.J., an, 1987, 3, 465–473, 130, hoehna, JSTOR, 2012.03.15 Low-density parity-check codes, Gallager, Robert G, Information Theory, IRE Transactions on, 1962, 1, 21–28, 8, hoehna, IEEE, 2014.11.28 Maximum-likelihood phylogenetic analysis under a covarion-like model, Galtier, Nicolas, mbe, 2001, 5, 866–873, 18, hoehna, SMBE, 2013.07.16 Inferring pattern and process: maximum-likelihood implementation of a nonhomogeneous model of DNA sequence evolution for phylogenetic analysis., Galtier, Nicolas and Gouy, Manolo, mbe, 1998, 7, 871–879, 15, hoehna, SMBE, 2013.07.16 Inferring phylogenies from DNA sequences of unequal base compositions, Galtier, Nicolas and Gouy, Manolo, pnas, 1995, 24, 11317–11321, 92, hoehna, National Acad Sciences, 2013.07.16 Sampling from the posterior distribution in generalized linear mixed models, Gamerman, D., Statistics and Computing, 1997, 1, 57–68, 7, shhn001, Springer, 2008.12.11 Markov chain Monte Carlo: stochastic simulation for Bayesian inference, Gamerman, D. and Lopes, H.F., Chapman & Hall/CRC, 2006, 1584885874, Hoehna, 2010.12.13 10.1007/b13243 Adaptive radiation: contrasting theory with data, Gavrilets, S. and Losos, J.B., Science, 2009, 5915, 732–737, 323, hoehna, American Association for the Advancement of Science, 2013.02.05 Dynamic patterns of adaptive radiation, Gavrilets, S. and Vose, A., pnas, 2005, 50, 18040, 102, hoehna, National Acad Sciences, 2012.08.01 10.1093/sysbio/syw060 Sampling-Based Approaches to Calculating Marginal Densities, Gelfand, Alan E. and Smith, Adrian F. M., jasa, 1990, 410, 398–409, 85, Stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm can be viewed as three alternative sampling- (or Monte Carlo-) based approaches to the calculation of numerical estimates of marginal probability distributions. The three approaches will be reviewed, compared, and contrasted in relation to various joint probability structures frequently encountered in applications. In particular, the relevance of the approaches to calculating Bayesian posterior densities for a variety of structured models will be discussed and illustrated., Copyright � 1990 American Statistical Association, 01621459, primary_article, Jun., 1990, shhn001, American Statistical Association, 2008.12.08 The Boxer, the Wrestler, and the Coin Flip, Gelman, A., The American Statistician, 2006, 2, 146–150, 60, hoehna, ASA, 2009.12.15 Bayesian Data Analysis, Gelman, A. and Carlin, J.B. and Stern, H.S. and Rubin, D.B., Chapman & Hall/CRC, 2003, 2, hoehna, 2012.10.01 Simulating normalizing constants: From importance sampling to bridge sampling to path sampling, Gelman, Andrew and Meng, Xiao-Li, Statistical science, 1998, 2, 163–185, 13, hoehna, JSTOR, 2015.04.16 Inference from iterative simulation using multiple sequences, Gelman, A. and Rubin, D.B., Statistical science, 1992, 4, 457–472, 7, 0883-4237, Hoehna, JSTOR, 2010.12.12 A single series from the Gibbs sampler provides a false sense of security, Gelman, A. and Rubin, D.B., Bayesian statistics, 1992, 625–632, 4, hoehna, Oxford University Press, 2011.07.19 Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images, Geman, Stuart and Geman, Donald, Pattern Analysis and Machine Intelligence, IEEE Transactions on, 1984, 6, 721–741, shhn001, IEEE, 2009.01.19 Late Miocene large mammals from Yulafli, Thrace region, Turkey, and their biogeographic implications, Geraads, Denis and Kaya, Tanju and Mayda, Serdar and others, Acta Palaeontologica Polonica, 2005, 3, 523–544, 50 The conditioned reconstructed process, Gernhard, T., jtb, 2008, 4, 769–778, 253, hoehna, Elsevier, Advances in the Birth-Death process. A new model for estimating prior and simulations., 2009.07.27 Evaluating the accuracy of sampling-based approaches to calculating posterior moments. In Bayesian Statistics 4.(Eds JM Bernardo, JO Berger, AP Dawid, and A. FM Smith.) pp. 169–193, Geweke, J., 1992, Hoehna, Oxford University Press, Oxford, UK, 2010.11.17 Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments, Geweke, J., Federal Reserve Bank of Minneapolis, Research Department, 1991, hoehna, 2012.07.27 Practical Markov Chain Monte Carlo, Geyer, Charles J., Statistical Science, 1992, 4, 473–483, 7, Markov chain Monte Carlo using the Metropolis-Hastings algorithm is a general method for the simulation of stochastic processes having probability densities known up to a constant of proportionality. Despite recent advances in its theory, the practice has remained controversial. This article makes the case for basing all inference on one long run of the Markov chain and estimating the Monte Carlo error by standard nonparametric methods well-known in the time-series and operations research literature. In passing it touches on the Kipnis-Varadhan central limit theorem for reversible Markov chains, on some new variance estimators, on judging the relative efficiency of competing Monte Carlo schemes, on methods for constructing more rapidly mixing Markov chains and on diagnostics for Markov chain Monte Carlo., Copyright © 1992 Institute of Mathematical Statistics, 08834237, primary_article, Nov., 1992, shhn001, Institute of Mathematical Statistics, A general overview over the use of Markov Chain Monte Carlo. Compares single long runs to multiple short ones. Gives also some recommendations about convergence. Uses also the diagnosis of the golden runs., 2008.06.19 Markov Chain Monte Carlo in Practice, Gilks, W.R. and Richardson, S. and Spiegelhalter, DJ, Chapman & Hall/CRC, 1996, shhn001, 2009.01.19 A language and program for complex Bayesian modelling, Gilks, WR and Thomas, A. and Spiegelhalter, DJ, The Statistician, 1994, 1, 169–177, 43, Hoehna, Blackwell Publishers, 2010.03.27 Wickham, Hadley, ggplot2: Elegant Graphics for Data Analysis, Springer-Verlag New York, 2016, 978-3-319-24277-4, http://ggplot2.org 10.1111/2041-210X.12628 Island Biogeography of Remote Archipelagoes, Gillespie, G. Rosemary and Baldwin, G. Bruce, The Theory of Island Biogeography Revisited, 2009, 358–387, Princeton University Press \textitZaragocyon daamsi n. gen. sp. nov., Ursidae primitif du Miocène inférieur d’Espagne, Ginsburg, L and Morales, J, Comptes Rendus de l’Académie des Sciences. Série 2. Sciences de la Terre et des Planètes, 1995, 9, 811–815, 321, Elsevier Les Hemicyoninae (Ursidae, Carnivora, Mammalia) et les formes apparentées du Miocène inférieur et moyen d’Europe occidentale, Ginsburg, Léonard and Morales, Jorge, Annales de Paléontologie, 1998, 1, Elsevier, 71–123, 84 Phylogenetic insights on adaptive radiation, Glor, R.E., arees, 2010, 251–270, 41, hoehna, Annual Reviews, 2013.02.05 A comparative analysis of selection schemes used in genetic algorithms, Goldberg, D.E. and Deb, K., Foundations of Genetic Algorithms, 1991, 69–93, 1, shhn001, 2009.01.20 On Phylogenetic Tests of Irreversible Evolution, Goldberg, Emma E. and Igić, Boris, evolution, 2008, 62, 2727–2741 Species selection maintains self-incompatibility, Goldberg, Emma E and Kohn, Joshua R and Lande, Russell and Robertson, Kelly A and Smith, Stephen A and Igić, Boris, Science, 2010, 6003, 493–495, 330, hoehna, American Association for the Advancement of Science, 2014.09.23 Phylogenetic Inference of Reciprocal Effects between Geographic Range Evolution and Diversification, Goldberg, Emma E and Lancaster, Lesley T and Ree, Richard H, sysbio, 2011, 4, 451–465, 60, hoehna, Oxford University Press, 2014.09.23 Tempo and Mode in Plant Breeding System Evolution, Goldberg, Emma E. and Igić, Boris, evolution, 2012, 66, 3701–3709 A codon-based model of nucleotide substitution for protein-coding DNA sequences., Goldman, N. and Yang, Z., mbe, 1994, 5, 725, 11, hoehna, SMBE, 2010.10.26 Minimum spanning trees and single linkage cluster analysis, Gower, John C and Ross, Gavin JS, Applied statistics, 54–64, 1969, JSTOR RNA PHYLOGENETIC INFERENCE WITH HETEROGENEOUS SUBSTITUTION MODELS, Gowri-Shankar, Vivek, University of Manchester, 2006, shhn001, 2008.03.24 A Reversible Jump Method for Bayesian Phylogenetic Inference with a Nonhomogeneous Substitution Model, Gowri-Shankar, V. and Rattray, M., mbe, 2007, 6, 1286, 24, shhn001, SMBE, First a short introduction about Bayesian MCMC for Phylogenetic Inference. Discussion about rooted and unrooted trees; why they used a rooted one. They used a rooted but not ultrametric tree. So in their description for the NNI and SPR no constraint of the nodeheights are given., 2008.03.24 10.1111/j.1096-0031.2008.00231.x Reading the entrails of chickens: molecular timescales of evolution and the illusion of precision, Graur, Dan and Martin, William, TRENDS in Genetics, 2004, 2, 80–86, 20, hoehna, Elsevier, 2015.08.07 Trans-dimensional markov chain monte carlo, Green, P.J., Highly structured stochastic systems, 2003, 179–198, 27, Hoehna, Oxford University Press, Reversible Jump MCMC, 2010.03.26 Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Green, P.J., Biometrika, 1995, 4, 711, 82, hoehna, Biometrika Trust, 2010.10.26 Using more than the oldest fossils: Dating Osmundaceae with three Bayesian clock approaches, Grimm, Guido W and Kapli, Paschalia and Bomfleur, Benjamin and McLoughlin, Stephen and Renner, Susanne S, sysbio, 2015, 3, 396–405, 64, hoehna, Oxford University Press, 2015.09.08 Probability and random processes, Grimmett, Geoffrey and Stirzaker, David, Oxford Univ Press, 1992, 2, hoehna, 2015.05.12 A branch-heterogeneous model of protein evolution for efficient inference of ancestral sequences, Groussin, M and Boussau, B and Gouy, M, sysbio, 2013, 4, 523–538, 62, hoehna, Oxford University Press, 2013.07.16 A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood, Guindon, Stephane and Gascuel, Olivier, sysbio, 2003, 5, 696–704, 52, Copyright © 2003 Society of Systematic Biologists, 10635157, primary_article, Oct., 2003, shhn001, Taylor & Francis, Ltd. for the Society of Systematic Biologists, An alternative to MCMC -> Hill Climbing. Gives also a introduction what else can be used and what is good and bad in ML, Hill-Climbing, MCMC..., 2008.04.25 Assessment of available anatomical characters for linking living mammals to fossil taxa in phylogenetic analyses, Guillerme, Thomas and Cooper, Natalie, Biology Letters, 12, 5, 20151003, 2016, The Royal Society http://dx.doi.org/10.1016/j.jtbi.2015.06.005 Likelihood Inference of Non-Constant Diversification Rates with Incomplete Taxon Sampling, Höhna, Sebastian, pone, 2014, 1, e84184, 9, hoehna, Public Library of Science, 2013.10.13 Fast simulation of reconstructed phylogenies under global time-dependent birth-death processes, Höhna, Sebastian, bi, 2013, 11, 1367–1374, 29, hoehna, Oxford Univ Press, 2013.01.11 New Efficient Algorithms for Bayesian Phylogenetic Inference Using Markov Chain Monte Carlo, Höhna, Sebastian, The Universtiy of Auckland, 2009, The University of Auckland, Department of Computer Science, Private Bag 92019, Auckland, New Zealand., feb, Master Thesis, hoehna, 2009.04.23, 2 Clock-Constrained Tree Proposal Operators in Bayesian Phylogenetic Inference, Höhna, Sebastian and Defoin-Platel, M. and Drummond, A.J., 8th IEEE International Conference on BioInformatics and BioEngineering, 2008. BIBE 2008, 2008, 1–7, hoehna, 2009.04.23 Guided Tree Topology Proposals for Bayesian Phylogenetic Inference, Höhna, Sebastian and Drummond, Alexei J., sysbio, 2012, 1, 1–11, 61, hoehna, Oxford University Press, 2011.07.11 10.1093/sysbio/syu039 Inferring speciation and extinction rates under different species sampling schemes, Höhna, Sebastian and Stadler, Tanja and Ronquist, Fredrik and Britton, Tom, mbe, 2011, 9, 2577–2589, 28, The birth-death process is widely used in phylogenetics to model speciation and extinction. Recent studies have shown that the inferred rates are sensitive to assumptions about the sampling probability of lineages. Here, we examine the effect of the method used to sample lineages. Whereas previous studies have assumed random sampling, we consider two extreme cases of biased sampling: ???diversified sampling???, where tips are selected to maximize diversity, and ???cluster sampling???, where sample diversity is minimized. Diversified sampling appears to be standard practice, e.g., in analyses of higher taxa, while cluster sampling may occur under special circumstances, e.g., in studies of geographically defined floras or faunas. Using both simulations and analyses of empirical data, we show that inferred rates may be heavily biased if the sampling strategy is not modeled correctly. In particular, when a diversified sample is treated as if it were a random or complete sample, the extinction rate is severely underestimated, often close to 0. Such dramatic errors may lead to serious consequences, e.g. if estimated rates are used in assessing the vulnerability of threatened species to extinction. Using Bayesian model testing across 18 empirical data sets, we show that diversified sampling is commonly a better fit to the data than complete, random or cluster sampling. Inappropriate modeling of the sampling method may at least partly explain anomalous results that have previously been attributed to variation over time in birth and death rates., http://mbe.oxfordjournals.org/content/early/2011/04/10/molbev.msr095.full.pdf+html 10.1093/sysbio/syw021 DRAM: efficient adaptive MCMC, Haario, Heikki and Laine, Marko and Mira, Antonietta and Saksman, Eero, Statistics and Computing, 2006, 4, 339–354, 16, hoehna, Springer, 2015.06.16 Adaptive proposal distribution for random walk Metropolis algorithm, Haario, Heikki and Saksman, Eero and Tamminen, Johanna, Computational Statistics, 1999, 3, 375–396, 14, hoehna, Citeseer, 2015.05.19 Time series analysis, Hamilton, J.D., Cambridge Univ Press, 1994, 10, hoehna, 2011.07.19 Monte Carlo methods, Hammersley, J.M. and Handscomb, D.C., Methuen, 1964, shhn001, 2008.09.09 Stabilizing selection and the comparative analysis of adaptation, Hansen, Thomas F, Evolution, 1997, 5, 1341–1351, 51, hoehna, JSTOR, 2015.02.26 GEIGER: investigating evolutionary radiations, Harmon, L.J. and Weir, J.T. and Brock, C.D. and Glor, R.E. and Challenger, W., bi, 2008, 1, 129–131, 24, hoehna, Oxford Univ Press, 2012.09.25 Among-Character Rate Variation Distributions in Phylogenetic Analysis of Discrete Morphological Characters, Harrison, Luke B and Larsson, Hans CE, sysbio, 2015, 2, 307-324, 64, hoehna, Oxford University Press, 2015.02.25 A Formal Basis for the Heuristic Determination of Minimum Cost Paths, Hart, PE and Nilsson, NJ and Raphael, B., Systems Science and Cybernetics, IEEE Transactions on, 1968, 2, 100–107, 4, shhn001, 2009.01.24 Sampling trees from evolutionary models, Hartmann, Klaas and Wong, Dennis and Stadler, Tanja, sysbio, 2010, 4, 465–476, 59, hoehna, Oxford University Press, 2013.09.04 Phylogenies Without Fossils, Harvey, Paul H. and May, Robert M. and Nee, Sean, evolution, 1994, 3, 523–529, 48, Phylogenies that are reconstructed without fossil material often contain approximate dates for lineage splitting. For example, particular nodes on molecular phylogenies may be dated by known geographic events that caused lineages to split, thereby calibrating a molecular clock that is used to date other nodes. On the one hand, such phylogenies contain no information about lineages that have become extinct. On the other hand, they do provide a potentially useful testing ground for ideas about evolutionary processes. Here we first ask what such reconstructed phylogenies should be expected to look like under a birth-death process in which the birth and death parameters of lineages remain constant through time. We show that it is possible to estimate both the birth and death rates of lineages from the reconstructed phylogenies, even though they contain no explicit information about extinct lineages. We also show how such phylogenies can reveal mass extinctions and how their characteristic footprint can be distinguished from similar ones produced by density-dependent cladogenesis., Copyright ? 1994 Society for the Study of Evolution, 00143820, primary_article, Jun., 1994, hoehna, Society for the Study of Evolution, 2009.09.25 The comparative method in evolutionary biology, Harvey, Paul H and Pagel, Mark D, Oxford university press Oxford, 1991, 239, hoehna, 2015.01.20 Dating of the Human-Ape Splitting by a molecular Clock of Mitochondrial DNA, Hasegawa, M. and Kishino, H. and Yano, T., jme, 1985, 2, 160–174, 22, shhn001, Springer, 2008.12.02 The Elements of Statistical Learning, Hastie, Trevor and Tibshirani, Robert and Friedman, Jerome, Springer Series in Statistics, 2009, hoehna, 2012.07.27 Monte Carlo Sampling Methods Using Markov Chains and Their Applications, Hastings, W. K., Biometrika, 1970, 1, 97–109, 57, A generalization of the sampling method introduced by Metropolis et al. (1953) is presented along with an exposition of the relevant theory, techniques of application and methods and difficulties of assessing the error in Monte Carlo estimates. Examples of the methods, including the generation of random orthogonal matrices and potential applications of the methods to numerical problems arising in statistics, are discussed., Copyright © 1970 Biometrika Trust, 00063444, primary_article, Apr., 1970, shhn001, Biometrika Trust, 2008.03.24 A hierarchical Bayesian model for calibrating estimates of species divergence times, Heath, Tracy A, sysbio, 2012, 5, 793–809, 61, hoehna, Oxford University Press, 2013.05.08 Bayesian inference of species divergence times, Heath, T. A. and Moore, B. R., Bayesian Phylogenetics: Methods, Algorithms, and Applications, Chapman & Hall/CRC, 2014, Boca Raton, FL, Chen, M.-H. and Kuo, L. and Lewis, P. O., 277–318, Chapman & Hall/CRC Mathematical and Computational Biology The fossilized birth-death process for coherent calibration of divergence-time estimates, Heath, Tracy A and Huelsenbeck, John P and Stadler, Tanja, pnas, 2014, 29, E2957–E2966, 111, hoehna, National Acad Sciences, 2015.05.31 Taxon sampling and the accuracy of phylogenetic analyses, Heath, T.A. and Hedtke, S.M. and Hillis, D.M., Journal of Systematics and Evolution, 2008, 3, 239–257, 46, hoehna, 2012.07.27 A Dirichlet Process Prior for Estimating Lineage-Specific Substitution Rates, Heath, T.A. and Holder, M.T. and Huelsenbeck, J.P., mbe, 2012, 3, 939–955, 29, hoehna, SMBE, 2012.07.27 Taxon sampling affects inferences of macroevolutionary processes from phylogenetic trees, Heath, T.A. and Zwickl, D.J. and Kim, J. and Hillis, D.M., sysbio, 2008, 1, 160–166, 57, hoehna, Oxford University Press, 2012.07.27 Precision of molecular time estimates, Hedges, S Blair and Kumar, Sudhir, TRENDS in Genetics, 2004, 5, 242–247, 20, hoehna, Elsevier, 2015.08.07 Genomic clocks and evolutionary timescales, Hedges, S Blair and Kumar, Sudhir, TRENDS in Genetics, 2003, 4, 200–206, 19, hoehna, Elsevier, 2015.08.07 Evolutionary rate analyses of orthologs and paralogs from 12 Drosophila genomes, Heger, Andreas and Ponting, Chris P, Genome research, 2007, 12, 1837–1849, 17, hoehna, Cold Spring Harbor Lab, 2013.08.12 Simulation run length control in the presence of an initial transient, Heidelberger, P. and Welch, P.D., Operations Research, 1983, 6, 1109–1144, 31, 0030-364X, Hoehna, JSTOR, 2011.02.08 \textitProsansanosmilus peregrinus, ein neuer machairodontider Felidae aus dem Miozän Deutschlands und Frankreichs, Heizmann, E and Ginsburg, L and Bulot, C, Stuttgarter Beitr. Naturk. B, 1980, 1–27, 58 Bayesian inference of species trees from multilocus data, Heled, J. and Drummond, A.J., mbe, 2010, 3, 570, 27, hoehna, SMBE, 2011.07.12 Bayesian inference of population size history from multiple loci, Heled, Joseph and Drummond, Alexei, bmcevobio, 2008, 1, 289, 8, hoehna, BioMed Central Ltd, 2013.04.17 Calibrated Birth–Death Phylogenetic Time-Tree Priors for Bayesian Inference, Heled, Joseph and Drummond, Alexei J, sysbio, 2015, 3, 369–383, 64, hoehna, Oxford University Press, 2015.09.07 Calibrated tree priors for relaxed phylogenetics and divergence time estimation, Heled, Joseph and Drummond, Alexei J, Systematic Biology, 2012, 1, 138–149, 61, hoehna, Oxford University Press, 2015.09.07 Using phylogenetic trees to study speciation and extinction, Hey, J., evolution, 1992, 627–640, 46, hoehna, JSTOR, 2012.03.16 Analysis and Visualization of Tree Space, Hillis, D.M. and Heath, T.A. and John, K.S., sysbio, 2005, 3, 471–482, 54, shhn001, Taylor & Francis, 2009.01.22 Beyond fossil calibrations: realities of molecular clock practices in evolutionary biology, Hipsley, Christy A and Müller, Johannes, Frontiers in genetics, 2014, 138, 1–11, 5, hoehna, Frontiers Media SA, 2015.09.08 The changing face of the molecular evolutionary clock, Ho, Simon YW, Trends in ecology & evolution, 2014, 9, 496–503, 29, hoehna, Elsevier, 2015.08.07 Calibrating molecular estimates of substitution rates and divergence times in birds, Ho, Simon YM, Journal of Avian Biology, 2007, 4, 409–414, 38, hoehna, Wiley Online Library, 2015.08.06 Molecular-clock methods for estimating evolutionary rates and timescales, Ho, Simon YW and Duchêne, Sebastián, Molecular ecology, 2014, 24, 5947–5965, 23, hoehna, Wiley Online Library, 2015.08.07 Simulating and detecting autocorrelation of molecular evolutionary rates among lineages, Ho, Simon YW and Duchêne, Sebastián and Duchêne, David, Molecular ecology resources, 2014, hoehna, Wiley Online Library, 2015.10.22 Biogeographic calibrations for the molecular clock, Ho, Simon YW and Tong, K Jun and Foster, Charles SP and Ritchie, Andrew M and Lo, Nathan and Crisp, Michael D, Biology Letters, 11, 9, 20150194, 2015, The Royal Society Molecular clocks: when timesare a-changin’, Ho, Simon YW and Larson, Greger, TRENDS in Genetics, 2006, 2, 79–83, 22, hoehna, Elsevier, 2015.08.07 Accounting for calibration uncertainty in phylogenetic estimation of evolutionary divergence times, Ho, Simon YW and Phillips, Matthew J, Systematic Biology, 2009, syp035, hoehna, Oxford University Press, 2015.08.07 Evidence for time dependency of molecular rate estimates, Ho, Simon YW and Shapiro, Beth and Phillips, Matthew J and Cooper, Alan and Drummond, Alexei J, sysbio, 2007, 3, 515–522, 56, hoehna, Oxford University Press, 2015.02.25 Successive radiations, not stasis, in the South American primate fauna, Hodgson, Jason A and Sterner, Kirstin N and Matthews, Luke J and Burrell, Andrew S and Jani, Rachana A and Raaum, Ryan L and Stewart, Caro-Beth and Disotell, Todd R, pnas, 2009, 14, 5534–5539, 106, hoehna, National Acad Sciences, 2015.07.30 Phylogeny estimation: traditional and Bayesian approaches, Holder, M. and Lewis, P.O., Nature Reviews Genetics, 2003, 4, 275, 4, shhn001, Nature Publishing Group, 2008.12.03 A justification for reporting the majority-rule consensus tree in Bayesian phylogenetics, Holder, Mark T and Sukumaran, Jeet and Lewis, Paul O, sysbio, 2008, 5, 814–821, 57, hoehna, Oxford University Press, 2013.05.06 Indel-associated mutation rate varies with mating system in flowering plants, Hollister, Jesse D and Ross-Ibarra, Jeffrey and Gaut, Brandon S, mbe, 2010, 2, 409–416, 27, hoehna, SMBE, 2013.08.05 Using guide trees to construct multiple-sequence evolutionary HMMs, Holmes, Ian, bi, 2003, suppl 1, i147–i157, 19, hoehna, Oxford Univ Press, 2013.08.01 Evolutionary HMMs: a Bayesian approach to multiple alignment, Holmes, Ian and Bruno, William J, bi, 2001, 9, 803–820, 17, hoehna, Oxford Univ Press, 2013.08.01 Amazonia through time: Andean uplift, climate change, landscape evolution, and biodiversity, Hoorn, Carina and Wesselingh, FP and Ter Steege, H and Bermudez, MA and Mora, A and Sevink, J and Sanmartı́n, I and Sanchez-Meseguer, A and Anderson, CL and Figueiredo, JP and others, science, 2010, 6006, 927–931, 330, hoehna, American Association for the Advancement of Science, 2013.05.14 RNA-based phylogenetic methods: application to mammalian mitochondrial RNA sequences, Hudelot, C. and Gowri-Shankar, V. and Jow, H. and Rattray, M. and Higgs, P.G., mpe, 2003, 2, 241–252, 28, shhn001, Elsevier, A Description about PhASE Version 1.1, 2008.03.24 Bayesian Phylogenetic Model Selection using Reversible Jump Markov Chain Monte Carlo, Huelsenbeck, J.P. and Larget, B. and Alfaro, M.E., mbe, 2004, 6, 1123, 21, hoehna, SMBE, 2010.10.21 Potential Applications and Pitfalls of Bayesian Inference of Phylogeny, Huelsenbeck, JP and Larget, B. and Miller, RE and Ronquist, F., sysbio, 2002, 5, 673–688, 51, shhn001, Taylor and Francis Ltd, 2008.03.24 MRBAYES: Bayesian inference of phylogenetic trees, Huelsenbeck, J.P. and Ronquist, F., bi, 2001, 8, 754–755, 17, shhn001, Oxford Univ Press, 2008.04.02 Bayesian Inference of Phylogeny and Its Impact on Evolutionary Biology, Huelsenbeck, J.P. and Ronquist, F. and Nielsen, R. and Bollback, J.P., Science, 2001, 5550, 2310 – 2314, 294, shhn001, 2008.04.02 Performance of phylogenetic methods in simulation, Huelsenbeck, J. P., sysbio, 1995, 17–48, 44, hoehna, 2013.08.01 10.1080/10635150802166046 Empirical and hierarchical Bayesian estimation of ancestral states, Huelsenbeck, John P and Bollback, Jonathan P, sysbio, 2001, 3, 351–366, 50, hoehna, Oxford University Press, 2013.05.31 Combining data in phylogenetic analysis, Huelsenbeck, John P and Bull, JJ and Cunningham, Clifford W, tee, 1996, 4, 152–158, 11, hoehna, Elsevier, 2015.02.25 Bayesian estimation of positively selected sites, Huelsenbeck, John P and Dyer, Kelly A, jme, 2004, 6, 661–672, 58, hoehna, Springer, 2013.08.10 Parametric bootstrapping in molecular phylogenetics: applications and performance, Huelsenbeck, JOHN P and Hillis, DAVID M and Jones, ROBERT, Molecular zoology: advances, strategies, and protocols, 1996, 19–45, 3, hoehna, Wiley-Liss, New York, NY, 2013.04.19 10.1073/pnas.0508279103 A compound Poisson process for relaxing the molecular clock, Huelsenbeck, J. P. and Larget, B. and Swofford, D. L., genetics, 2000, 1879–1892, 154, hoehna, 2013.08.01 10.1080/10635150490522629 Detecting correlation between characters in a comparative analysis with uncertain phylogeny, Huelsenbeck, John P and Rannala, Bruce, evolution, 2003, 6, 1237–1247, 57, hoehna, Wiley Online Library, 2015.01.22 Phylogenetic methods come of age: testing hypotheses in an evolutionary context, Huelsenbeck, John P and Rannala, Bruce, Science, 1997, 5310, 227–232, 276, hoehna, American Association for the Advancement of Science, 2013.08.10 Accommodating phylogenetic uncertainty in evolutionary studies, Huelsenbeck, John P and Rannala, Bruce and Masly, John P, Science, 2000, 5475, 2349–2350, 288, hoehna, American Association for the Advancement of Science, 2013.05.31 An adaptive scheduling scheme for calculating Bayes factors with thermodynamic integration using Simpson?s rule, Hug, Sabine and Schwarzfischer, Michael and Hasenauer, Jan and Marr, Carsten and Theis, Fabian J, Statistics and Computing, 2015, 1–15, hoehna, Springer, 2015.03.16 The impact of the representation of fossil calibrations on Bayesian estimation of species divergence times, Inoue, J. and Donoghue, P.C.J. and Yang, Z., sysbio, 2010, 1, 74–89, 59, hoehna, 2010.04.21 Approximate Bayesian Computation of diversification rates from molecular phylogenies: introducing a new efficient summary statistic, the nLTT, Janzen, Thijs and Höhna, Sebastian and Etienne, Rampal S, Methods in Ecology and Evolution, 2015, 5, 566–575, 6, hoehna, Wiley Online Library, 2015.06.16 The Theory of Probability, Jeffreys, Harold, Oxford University Press, 1961, hoehna, 2015.01.20 Blocking Gibbs sampling in very large probabilistic expert systems, Jensen, C.S. and Kjærulff, U. and Kong, A., International Journal of Human Computer Studies, 1995, 6, 647–666, 42, Hoehna, Citeseer, 2010.10.12 The global diversity of birds in space and time, Jetz, W. and Thomas, GH and Joy, JB and Hartmann, K. and Mooers, AO, Nature, 2012, 7424, 444–448, 491, hoehna, Nature Publishing Group, 2013.01.11 The first skull of the earliest giant panda, Jin, Changzhu and Ciochon, Russell L and Dong, Wei and Hunt, Robert M and Liu, Jinyi and Jaeger, Marc and Zhu, Qizhi, pnas, 2007, 26, 10932–10937, 104 On the Markov chain central limit theorem, Jones, G.L., Probability surveys, 2004, 299–320, 1, 1549-5787, Hoehna, IMS and ISI/Bernoulli Society, 2011.03.03 Fixed-width output analysis for Markov chain Monte Carlo, Jones, G.L. and Haran, M. and Caffo, B.S. and Neath, R., jasa, 2006, 476, 1537–1547, 101, 0162-1459, Hoehna, ASA, 2010.12.13 The effects of alignment error and alignment filtering on the sitewise detection of positive selection, Jordan, Gregory and Goldman, Nick, mbe, 2012, 4, 1125–1139, 29, hoehna, SMBE, 2013.08.05 Graphical models, Jordan, M.I., Statistical Science, 2004, 1, 140–155, 19, hoehna, JSTOR, 2010.10.20 Interactive web-based visualization of phylogenetic trees using Phylogeny. IO, Jovanovic, Nikola and Mikheyev, Alexander S, 2016, PeerJ Preprints, 4, e2579v1, PeerJ Inc. San Francisco, USA Bayesian Phylogenetics Using an RNA Substitution Model Applied to Early Mammalian Evolution, Jow, H. and Hudelot, C. and Rattray, M. and Higgs, P. G., mbe, 2002, 9, 1591-1601, 19, We study the phylogeny of the placental mammals using molecular data from all mitochondrial tRNAs and rRNAs of 54 species. We use probabilistic substitution models specific to evolution in base paired regions of RNA. A number of these models have been implemented in a new phylogenetic inference software package for carrying out maximum likelihood and Bayesian phylogenetic inferences. We describe our Bayesian phylogenetic method which uses a Markov chain Monte Carlo algorithm to provide samples from the posterior distribution of tree topologies. Our results show support for four primary mammalian clades, in agreement with recent studies of much larger data sets mainly comprising nuclear DNA. We discuss some issues arising when using Bayesian techniques on RNA sequence data., http://mbe.oxfordjournals.org/cgi/reprint/19/9/1591.pdf, shhn001, Introduction of PhASE. Our only condition is that the Markov chain be ergodic, i.e., that there is a nonzero probability of reaching any point in the state-space starting from any other point in a finite number of steps. Description of their Conitnous Change proposal and the NNI and SPR. the CC is similar to our, but smother and works similar to a NNI when it causes a topology change., 2008.03.24 A divergence dating analysis of turtles using fossil calibrations: an example of best practices, Joyce, Walter G and Parham, James F and Lyson, Tyler R and Warnock, Rachel CM and Donoghue, Philip CJ, Journal of Paleontology, 2013, 4, 612–634, 87, hoehna, The Paleontological Society, 2015.09.08 Evolution of Protein Molecules, Jukes, TH and Cantor, CR, Mammalian Protein Metabolism, 1969, 21–132, 3, shhn001, New York, 2008.12.02 Simultaneous reconstruction of evolutionary history and epidemiological dynamics from viral sequences with the birth–death SIR model, Kühnert, Denise and Stadler, Tanja and Vaughan, Timothy G and Drummond, Alexei J, Journal of the Royal Society Interface, 2014, 94, 20131106, 11, hoehna, The Royal Society, 2015.10.21 Bayes Factors, Kass, R.E. and Raftery, A.E., jasa, 1995, 773–795, 90, hoehna, JSTOR, 2011.09.14 The anatomy of Dolichocebus gaimanensis, a stem platyrrhine monkey from Argentina, Kay, Richard F and Fleagle, JG and Mitchell, TRT and Colbert, Matthew and Bown, Tom and Powers, Dennis W, Journal of Human Evolution, 2008, 3, 323–382, 54, hoehna, Elsevier, 2015.07.30 A Generalized Markov Sampler, Keith, J.M. and Kroese, D.P. and Bryant, D., Methodology and Computing in Applied Probability, 2004, 1, 29–53, 6, shhn001, Springer, 2008.03.21 Stochastic Processes and Population Growth, Kendall, David G., Journal of the Royal Statistical Society. Series B (Methodological), 1949, 2, 230–282, 11, Copyright ? 1949 Royal Statistical Society, primary_article, 1949, hoehna, Blackwell Publishing for the Royal Statistical Society, Birth-Death process., 2009.07.27 On the Generalized "Birth-and-Death" Process, Kendall, David G., The Annals of Mathematical Statistics, 1948, 1, 1–15, 19, The importance of stochastic processes in relation to problems of population growth was pointed out by W. Feller [1] in 1939. He considered among other examples the "birth-and-death" process in which the expected birth and death rates (per head of population per unit of time) were constants, bo and do, say. In this paper, I shall give the complete solution of the equations governing the generalised birth-and-death process in which the birth and death rates b(t) and d(t) may be any specified functions of the time. The mathematical method employed starts from M. S. Bartlett’s idea of replacing the differential-difference equations for the distribution of the population size by a partial differential equation for its generating function. For an account of this technique,1 reference may be made to Bartlett’s North Carolina lectures [2]. The formulae obtained lead to an expression for the probability of the ultimate extinction of the population, and to the necessary and sufficient condition for a birth-and-death process to be of "transient" type. For transient processes the distribution of the cumulative population is also considered, but here in general it is not found possible to do more than evaluate its mean and variance as functions of t, although a complete solution (including the determination of the asymptotic form of the distribution as t tends to infinity) is obtained for the simple process in which the birth and death rates are independent of the time. It is shown that a birth-and-death process can be constructed to give an expected population size \bar n_t which is any desired function of the time t, and among the many possible solutions the unique one is determined which makes the fluctuation, Var(nt), a minimum for all. The general theory is illustrated with reference of two examples. The first of these is the (b0, d1t) process introduced by N. Arley [3] in his study of the cascade showers associated with cosmic radiation; here the birth rate is constant and the death rate is a constant multiple of the "age, t, of the process. The \bar n_t -curve is then Gaussian in form, and the process is always of transient type. The second example is provided by the family of "periodic" processes, in which the birth and death rates are periodic functions of the time t. These appear well adapted to describe the response of population growth (or epidemic spread) to the influence of the seasons., Copyright ? 1948 Institute of Mathematical Statistics, primary_article, Mar., 1948, hoehna, Institute of Mathematical Statistics, First paper on Birth-Death process., 2009.07.27 ECOLOGICAL LIMITS ON DIVERSIFICATION OF THE HIMALAYAN CORE CORVOIDEA, Kennedy, J.D. and Weir, J.T. and Hooper, D.M. and Thomas Tietze, D. and Martens, J. and Price, T.D., evolution, 2012, hoehna, Wiley Online Library, 2012.08.01 A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences, Kimura, M., jme, 1980, 2, 111–120, 16, shhn001, Springer, 2008.12.02 On the Genealogy of Large Populations, Kingman, J. F. C., Journal of Applied Probability, 1982, 27–43, 19, A new Markov chain is introduced which can be used to describe the family relationships among n individuals drawn from a particular generation of a large haploid population. The properties of this process can be studied, simultaneously for all n, by coupling techniques. Recent results in neutral mutation theory are seen as consequences of the genealogy described by the chain., Copyright ? 1982 Applied Probability Trust, 00219002, primary_article, 1982, Essays in Statistical Science, hoehna, Applied Probability Trust, Origin of Kingman Coalescent Theory for population genetics., 2009.07.23 Maximum likelihood inference of protein phylogeny and the origin of chloroplasts, Kishino, Hirohisa and Miyata, Takashi and Hasegawa, Masami, jme, 1990, 2, 151–160, 31, hoehna, Springer, 2016.03.20 Performance of a divergence time estimation method under a probabilistic model of rate evolution, Kishino, Hirohisa and Thorne, Jeffrey L and Bruno, William J, mbe, 2001, 3, 352–361, 18, hoehna, SMBE, 2014.06.04 Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo, Kloek, T. and van Dijk, H.K., Econometrica, 1978, 1, 1–19, 46, shhn001, 2008.09.09 Probabilistic Graphical Models: Principles and Techniques, Koller, D. and Friedman, N., The MIT Press, 2009, Cambridge, hoehna, 2010.10.27 Selection on the Protein-Coding Genome, Kosiol, Carolin and Anisimova, Maria, Evolutionary Genomics, Springer, 2012, 113–140, hoehna, 2013.08.10 Patterns of positive selection in six Mammalian genomes, Kosiol, Carolin and Vinař, Tomáš and da Fonseca, Rute R and Hubisz, Melissa J and Bustamante, Carlos D and Nielsen, Rasmus and Siepel, Adam, pgenetics, 2008, 8, e1000144, 4, hoehna, Public Library of Science, 2013.08.10 Mitochondrial genomes reveal an explosive radiation of extinct and extant bears near the Miocene-Pliocene boundary, Krause, Johannes and Unger, Tina and Noçon, Aline and Malaspinas, Anna-Sapfo and Kolokotronis, Sergios-Orestis and Stiller, Mathias and Soibelzon, Leopoldo and Spriggs, Helen and Dear, Paul H and Briggs, Adrian W and others, BMC Evolutionary Biology, 2008, 1, 220, 8, BioMed Central Ltd 10.1109/18.910572 Inferring the rates of branching and extinction from molecular phylogenies, Kubo, Takuya and Iwasa, Yoh, Evolution, 1995, 4, 694–704, 49, hoehna, Wiley, 2014.03.03 A Simple Polytomy Resolver for Dated Phylogenies, Kuhn, Tyler S. and Mooers, Arne Ø. and Thomas, Gavin H., Methods in Ecology and Evolution, 2, 427–436, 2011 A simulation comparison of phylogeny algorithms under equal and unequal evolutionary rates, Kuhner, M.K. and Felsenstein, J., mbe, 1994, 3, 459–468, 11, shhn001, A comparison about parsimony, compatibility, maximum likelihood, Fitch-Margoliash and Neighbor-Joining, 2008.04.02 10.1093/bioinformatics/btk051 10.1534/genetics.106.056457 Efficiency of Markov Chain Monte Carlo Tree Proposals in Bayesian Phylogenetics, Lakner, Clemens and van der Mark, Paul and Huelsenbeck, John P. and Larget, Bret and Ronquist, Frederik, sysbio, 2008, 1, 86–103, 57, shhn001, Taylor & Francis, 2008.03.25 The contour of splitting trees is a Lévy process, Lambert, Amaury, The Annals of Probability, 2010, 1, 348–395, 38, hoehna, Institute of Mathematical Statistics, 2013.09.04 Phylogenetic analysis accounting for age-dependent death and sampling with applications to epidemics, Lambert, Amaury and Alexander, Helen K and Stadler, Tanja, jtb, 2014, 60–70, 352, hoehna, Elsevier, 2015.09.22 Birth–death models and coalescent point processes: the shape and probability of reconstructed phylogenies, Lambert, Amaury and Stadler, Tanja, tpb, 2013, 113–128, 90, hoehna, Elsevier, 2015.09.22 A new method for calculating evolutionary substitution rates, Lanave, C. and Preparata, G. and Sacone, C. and Serio, G., jme, 1984, 1, 86–93, 20, shhn001, Springer, 2009.02.05 A note on bootstraps and robustness, Lancaster, T., Disponıvel em:< http://www. econ. brow n. edu/= tl/pa pe rs/robus t. pdf>. Acesso em: dez, 2007, hoehna, 2009.10.13 Initial sequencing and analysis of the human genome, Lander, Eric S and Linton, Lauren M and Birren, Bruce and Nusbaum, Chad and Zody, Michael C and Baldwin, Jennifer and Devon, Keri and Dewar, Ken and Doyle, Michael and FitzHugh, William and others, Nature, 2001, 6822, 860–921, 409, hoehna, Nature Publishing Group, 2013.08.11 10.1093/sysbio/syw040 Bayesian Analysis of Biogeography when the Number of Areas is Large, Landis, Michael J and Matzke, Nicholas J and Moore, Brian R and Huelsenbeck, John P, sysbio, 2013, 6, 789–804, 62, hoehna, Oxford University Press, 2014.04.08 Phylogenetic analysis using Lévy processes: finding jumps in the evolution of continuous traits, Landis, Michael J and Schraiber, Joshua G and Liang, Mason, sysbio, 2013, 2, 193–204, 62, hoehna, Oxford University Press, 2013.08.12 PartitionFinder: combined selection of partitioning schemes and substitution models for phylogenetic analyses, Lanfear, Robert and Calcott, Brett and Ho, Simon YW and Guindon, Stephane, mbe, 2012, 6, 1695–1701, 29, hoehna, SMBE, 2015.02.25 Markov Chain Monte Carlo Algorithms for the Bayesian Analysis of Phylogenetic Trees, Larget, B and Simon, DL, mbe, 1999, 6, 750-759, 16, http://mbe.oxfordjournals.org/cgi/reprint/16/6/750.pdf, shhn001, Short summary about Bayesian MCMC and the three research groups working on it. Introduction into their Local and Global tree proposal operators. They use the canonical representation of the tree and change few or all node heights. This leads to topology changes which are reconstructed regarding the representation. In their experience one algorithm can not be sufficient for good mixing. They discuss the use of Bayesian MCMC and Maximum Likelihood and Bootstrapping approaches. Their algorithms are available in BAMBE (Bayesian Analysis in Molecular Biology and Evolution), 2008.03.24 Interaction between selection and biased gene conversion in mammalian protein-coding sequence evolution revealed by a phylogenetic covariance analysis, Lartillot, Nicolas, mbe, 2013, 2, 356–368, 30, hoehna, SMBE, 2013.08.11 Conjugate Gibbs Sampling for Bayesian Phylogenetic Models, Lartillot, N., Journal of Computational Biology, 2006, 10, 1701–1722, 13, shhn001, Mary Ann Liebert, Inc. 2 Madison Avenue Larchmont, NY 10538 USA, 2009.02.16 Suppression of long-branch attraction artefacts in the animal phylogeny using a site-heterogeneous model, Lartillot, Nicolas and Brinkmann, Henner and Philippe, Hervé, BMC evolutionary biology, 2007, Suppl 1, S4, 7, hoehna, BioMed Central Ltd, 2014.12.01 JOINT RECONSTRUCTION OF DIVERGENCE TIMES AND LIFE-HISTORY EVOLUTION IN PLACENTAL MAMMALS USING A PHYLOGENETIC COVARIANCE MODEL, Lartillot, Nicolas and Delsuc, Frédéric, evolution, 2012, 6, 1773–1787, 66, hoehna, Wiley Online Library, 2013.05.31 PhyloBayes 3: a Bayesian software package for phylogenetic reconstruction and molecular dating, Lartillot, N. and Lepage, T. and Blanquart, S., bi, 2009, 17, 2286, 25, hoehna, Oxford Univ Press, 2011.07.11 Computing Bayes factors using thermodynamic integration, Lartillot, N. and Philippe, H., sysbio, 2006, 2, 195, 55, Hoehna, 2010.10.12 A phylogenetic model for investigating correlated evolution of substitution rates and continuous phenotypic characters, Lartillot, Nicolas and Poujol, Raphaël, mbe, 2011, 1, 729–744, 28, hoehna, SMBE, 2013.08.11 PhyloBayes MPI: phylogenetic reconstruction with infinite mixtures of profiles in a parallel environment, Lartillot, Nicolas and Rodrigue, Nicolas and Stubbs, Daniel and Richer, Jacques, sysbio, 2013, 4, 611–615, 62, hoehna, Oxford University Press, 2014.04.05 Graphical models, Lauritzen, S.L., Oxford University Press, USA, 1996, Hoehna, 2010.03.27 Bayes Factors: What They Are and What They Are Not, Lavine, Michael and Schervish, Mark J, The American Statistician, 1999, 2, 119–122, 53, hoehna, Taylor & Francis, 2015.01.20 The accuracy of species tree estimation under simulation: a comparison of methods, Leaché, Adam D and Rannala, Bruce, sysbio, 2011, 2, 126–137, 60, hoehna, Oxford University Press, 2013.04.17 Introduction to algorithms, Leiserson, Charles E and Rivest, Ronald L and Stein, Clifford and Cormen, Thomas H, The MIT press, 2001, hoehna, 2013.07.17 Bayesian phylogeography finds its roots, Lemey, Philippe and Rambaut, Andrew and Drummond, Alexei J and Suchard, Marc A, pcb, 2009, 9, e1000520, 5, hoehna, Public Library of Science, 2015.02.27 A general comparison of relaxed molecular clock models, Lepage, T. and Bryant, D. and Philippe, H. and Lartillot, N., mbe, 2007, 12, 2669, 24, Hoehna, SMBE, 2010.03.26 Continuous and tractable models for the variation of evolutionary rates, Lepage, Thomas and Lawi, Stephan and Tupper, Paul and Bryant, David, Mathematical biosciences, 2006, 2, 216–233, 199, hoehna, Elsevier, 2016.03.20 Using an epidemiological model for phylogenetic inference reveals density dependence in HIV transmission, Leventhal, Gabriel E and Günthard, Huldrych F and Bonhoeffer, Sebastian and Stadler, Tanja, mbe, 2014, 1, 6–17, 31, hoehna, SMBE, 2015.09.22 Polytomies and Bayesian Phylogenetic Inference, Lewis, P.O. and Holder, M.T. and Holsinger, K.E., sysbio, 2005, 2, 241–253, 54, shhn001, Taylor & Francis, Description of the operators in use of P4., 2008.12.01 NCL: a C++ class library for interpreting data files in NEXUS format, Lewis, Paul O, bi, 2003, 17, 2330–2331, 19, hoehna, Oxford Univ Press, 2014.11.29 10.1080/106351501753462876 Posterior predictive Bayesian phylogenetic model selection, Lewis, Paul O and Xie, Wangang and Chen, Ming-Hui and Fan, Yu and Kuo, Lynn, sysbio, 2014, 3, 309–321, 63, hoehna, Oxford University Press, 2015.05.15 Phylogenetic Tree Construction Using Markov Chain Monte Carlo, Li, Shuying and Pearl, Dennis K. and Doss, Hani, jasa, 2000, 450, 493–508, 95, We describe a Bayesian method based on Markov chain simulation to study the phylogenetic relationship in a group of DNA sequences. Under simple models of mutational events, our method produces a Markov chain whose stationary distribution is the conditional distribution of the phylogeny given the observed sequences. Our algorithm strikes a reasonable balance between the desire to move globally through the space of phylogenies and the need to make computationally feasible moves in areas of high probability. Because phylogenetic information is described by a tree, we have created new diagnostics to handle this type of data structure. An important byproduct of the Markov chain Monte Carlo phylogeny building technique is that it provides estimates and corresponding measures of variability for any aspect of the phylogeny under study., Copyright © 2000 American Statistical Association, 01621459, primary_article, Jun., 2000, shhn001, American Statistical Association, 2008.04.25 Model averaging and Bayes factor calculation of relaxed molecular clocks in Bayesian phylogenetics, Li, Wai Lok Sibon and Drummond, Alexei J, mbe, 2012, 2, 751–761, 29, hoehna, SMBE, 2013.03.26 Evaluation of Bayesian models of substitution rate evolution?parental guidance versus mutual independence, Linder, Martin and Britton, Tom and Sennblad, Bengt, sysbio, 2011, 3, 329–342, 60, hoehna, Oxford University Press, 2014.01.23 When Can Decreasing Diversification Rates Be Detected with Molecular Phylogenies and the Fossil Record?, Liow, L.H. and Quental, T.B. and Marshall, C.R., sysbio, 2010, 6, 646, 59, hoehna, Oxford University Press, 2011.09.08 Monte Carlo Strategies in Scientific Computing, Liu, J.S., Springer, 2001, shhn001, 2009.02.03 Metropolized independent sampling with comparisons to rejection sampling and importance sampling, Liu, J.S., Statistics and Computing, 1996, 2, 113–119, 6, shhn001, Springer, 2009.02.08 The Collapsed Gibbs Sampler in Bayesian Computations With Applications to a Gene Regulation Problem, Liu, J.S., jasa, 1994, 427, 958–966, 89, shhn001, American Statistical Association, 2009.02.08 10.1093/biomet/83.3.681 BEST: Bayesian estimation of species trees under the coalescent model, Liu, Liang, bi, 2008, 21, 2542–2543, 24, hoehna, Oxford Univ Press, 2013.06.11 Species trees from gene trees: reconstructing Bayesian posterior distributions of a species phylogeny using estimated gene tree distributions, Liu, Liang and Pearl, Dennis K, sysbio, 2007, 3, 504–514, 56, hoehna, Oxford University Press, 2013.06.11 Estimating species trees using multiple-allele DNA sequence data, Liu, Liang and Pearl, Dennis K and Brumfield, Robb T and Edwards, Scott V, evolution, 2008, 8, 2080–2091, 62, hoehna, Wiley Online Library, 2013.04.17 Coalescent methods for estimating phylogenetic trees, Liu, Liang and Yu, Lili and Kubatko, Laura and Pearl, Dennis K and Edwards, Scott V, mpe, 2009, 1, 320, 53, hoehna, 2013.04.17 Estimating species phylogenies using coalescence times among sequences, Liu, Liang and Yu, Lili and Pearl, Dennis K and Edwards, Scott V, sysbio, 2009, 5, 468–477, 58, hoehna, Oxford University Press, 2013.04.17 10.1007/s00285-009-0260-0 Ancient DNA analysis reveals divergence of the cave bear, \textitUrsus spelaeus, and brown bear, \textitUrsus arctos, lineages, Loreille, Odile and Orlando, Ludovic and Patou-Mathis, Marylène and Philippe, Michel and Taberlet, Pierre and Hänni, Catherine, Current Biology, 2001, 3, 200–203, 11 Functional evolution of noncoding DNA, Ludwig, Michael Z, Current opinion in genetics & development, 2002, 6, 634–639, 12, hoehna, Elsevier, 2013.08.12 The BUGS book: A practical introduction to Bayesian analysis, Lunn, David and Jackson, Chris and Spiegelhalter, David J and Best, Nicky and Thomas, Andrew, CRC Press, 2012, 98, hoehna, 2013.10.10 The BUGS Project: Evolution, Critique and Future Directions, Lunn, David and Spiegelhalter, David and Thomas, Andrew and Best, Nicky, Statistics in Medicine, 2009, 25, 3049–3067, 28, hoehna, Wiley Online Library, 2013.05.31 WinBUGS – a Bayesian Modelling Framework: Concepts, Structure, and Extensibility, Lunn, David J and Thomas, Andrew and Best, Nicky and Spiegelhalter, David, Statistics and Computing, 2000, 4, 325–337, 10, hoehna, Springer, 2013.05.31 Probabilistic whole-genome alignments reveal high indel rates in the human and mouse genomes, Lunter, Gerton, bi, 2007, 13, i289–i296, 23, hoehna, Oxford Univ Press, 2013.08.11 Statistical alignment: Recent progress, new applications, and challenges, Lunter, Gerton and Drummond, Alexei J and Miklós, István and Hein, Jotun, Statistical methods in molecular evolution, Springer, 2005, 375–405, hoehna, 2013.08.01 Bayesian coestimation of phylogeny and sequence alignment, Lunter, G. and Miklós, I. and Drummond, A. and Jensen, J.L. and Hein, J., BMC Bioinformatics, 2005, 1, 83, 6, shhn001, BioMed Central, 2008.04.26 Bayesian phylogenetic inference under a statistical insertion-deletion model, Lunter, Gerton and Miklós, István and Drummond, Alexei and Jensen, Jens Ledet and Hein, Jotun, Algorithms in Bioinformatics, Springer, 2003, 228–244, hoehna, 2013.08.01 Uncertainty in homology inferences: assessing and improving genomic sequence alignment, Lunter, Gerton and Rocco, Andrea and Mimouni, Naila and Heger, Andreas and Caldeira, Alexandre and Hein, Jotun, Genome research, 2008, 2, 298–309, 18, hoehna, Cold Spring Harbor Lab, 2013.08.01 Alternatives to the Gibbs sampling scheme, Müller, Peter, Tech. report, Institute of Statistics and Decision Sciences, Duke University, 1992, shhn001, 2008.04.11 Theory of Island Biogeography., MacArthur, Robert H and Wilson, Edward O, Princeton University Press, 1967, 1 Estimating a binary character’s effect on speciation and extinction, Maddison, W.P. and Midford, P.E. and Otto, S.P., sysbio, 2007, 5, 701, 56, Hoehna, 2010.11.06 Gene trees in species trees, Maddison, Wayne P, sysbio, 1997, 3, 523–536, 46, hoehna, Oxford University Press, 2013.06.11 Mesquite: a modular system for evolutionary analysis. Version 2.5, Maddison, W. P. and ., D.R. Maddison., http://mesquiteproject.org, 2008, shhn001, 2009.01.12, http://mesquiteproject.org Confounding Asymmetries in Evolutionary Diversification and Character Change, Maddison, Wayne P., evolution, 2006, 60, 1743–1746 Inferring phylogeny despite incomplete lineage sorting, Maddison, Wayne P and Knowles, L Lacey, sysbio, 2006, 1, 21–30, 55, hoehna, Oxford University Press, 2013.10.14 10.1093/sysbio/syu070 10.1371/journal.pone.0110268 The difficulty of avoiding false positives in genome scans for natural selection, Mallick, Swapan and Gnerre, Sante and Muller, Paul and Reich, David, Genome research, 2009, 5, 922–933, 19, hoehna, Cold Spring Harbor Lab, 2013.08.10 High sensitivity to aligner and high rate of false positives in the estimates of positive selection in the 12 Drosophila genomes, Markova-Raina, Penka and Petrov, Dmitri, Genome research, 2011, 6, 863–874, 21, hoehna, Cold Spring Harbor Lab, 2013.08.10 Non-null Effects of the Null Range in Biogeographic Models: Exploring Parameter Estimation in the DEC Model, Massana, Kathryn A and Beaulieu, Jeremy M and Matzke, Nicholas J and O’Meara, Brian C, bioRxiv, 2015, 026914, Cold Spring Harbor Labs Journals Detecting amino acid sites under positive selection and purifying selection, Massingham, Tim and Goldman, Nick, genetics, 2005, 3, 1753–1762, 169, hoehna, Genetics Soc America, 2013.08.10 A geometric approach to tree shape statistics, Matsen, Frederick A., sysbio, 2006, 4, 652–661, 55, shhn001, Oxford University Press, 2009.01.22 Molecular phylogeny and evolution of prosimians based on complete sequences of mitochondrial DNAs, Matsui, Atsushi and Rakotondraparany, Felix and Munechika, Isao and Hasegawa, Masami and Horai, Satoshi, Gene, 2009, 1, 53–66, 441, hoehna, Elsevier, 2015.07.30 Founder-event speciation in BioGeoBEARS package dramatically improves likelihoods and alters parameter inference in dispersal–extinction–cladogenesis DEC analyses, Matzke, Nicholas J, Frontiers of Biogeography, 2012, 210, 4 Model Selection in Historical Biogeography Reveals that Founder-Event Speciation Is a Crucial Process in Island Clades, Matzke, Nicholas J, Systematic Biology, 63, 6, 951–970, 2014, Oxford University Press Phylogenetic Inference for Binary Data on Dendograms Using Markov Chain Monte Carlo, Mau, Bob and Newton, Michael A., Journal of Computational and Graphical Statistics, 1997, 1, 122–131, 6, Using a stochastic model for the evolution of discrete characters among a group of organisms, we derive a Markov chain that simulates a Bayesian posterior distribution on the space of dendograms. A transformation of the tree into a canonical cophenetic matrix form, with distinct entries along its superdiagonal, suggests a simple proposal distribution for selecting candidate trees "close" to the current tree in the chain. We apply the consequent Metropolis algorithm to published restriction site data on nine species of plants. The Markov chain mixes well from random starting trees, generating reproducible estimates and confidence sets for the path of evolution., Copyright © 1997 American Statistical Association, Institute of Mathematical Statistics and Interface Foundation of America, 10618600, primary_article, Mar., 1997, shhn001, American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of America, 2008.04.09 Bayesian Phylogenetic Inference via Markov Chain Monte Carlo Methods, Mau, B. and Newton, M.A. and Larget, B., Biometrics, 1999, 1, 1–12, 55, shhn001, JSTOR, They describe a new presentation, a binary, canonical one for the trees and the tree proposal operators for it., 2008.03.24 A Bayesian Approach for Detecting the Impact of Mass-Extinction Events on Molecular Phylogenies When Rates of Lineage Diversification May Vary, May, Michael R. and Höhna, S. and Moore, Brian R., mee, 2016, 8, 947–959, 7, hoehna, 2016.03.03 A Gamma mixture model better accounts for among site rate heterogeneity, Mayrose, Itay and Friedman, Nir and Pupko, Tal, bi, 2005, suppl 2, ii151–ii158, 21, hoehna, Oxford Univ Press, 2013.05.20 Site-Specific Evolutionary Rate Inference: Taking Phylogenetic Uncertainty into Account, Mayrose, I. and Mitchell, A. and Pupko, T., jme, 2005, 3, 345–353, 60, shhn001, Springer, Article describing McRate., 2008.12.02 Phylogenetic systematics and biogeography of hummingbirds: Bayesian and maximum likelihood analyses of partitioned data and selection of an appropriate partitioning strategy, McGuire, Jimmy A and Witt, Christopher C and Altshuler, Douglas L and Remsen, JV, sysbio, 2007, 5, 837–856, 56, hoehna, Oxford University Press, 2015.01.20 The ecological dynamics of clade diversification and community assembly, McPeek, M.A., an, 2008, 6, E270–E284, 172, hoehna, JSTOR, 2012.07.27 Simulating ratios of normalizing constants via a simple identity: a theoretical exploration, Meng, Xiao-Li and Wong, Wing Hung, Statistica Sinica, 1996, 4, 831–860, 6, hoehna, C/O DR SW CHENG, MANAG EDITOR DEPT STAT UNIV MANTOBA, WINNIPEG MB R3T 2N2, CANADA, 2015.04.16 Impacts of the Cretaceous Terrestrial Revolution and KPg extinction on mammal diversification, Meredith, R.W. and Janečka, J.E. and Gatesy, J. and Ryder, O.A. and Fisher, C.A. and Teeling, E.C. and Goodbla, A. and Eizirik, E. and Simão, T.L.L. and Stadler, T. and others, Science, 2011, 6055, 521–524, 334, hoehna, American Association for the Advancement of Science, 2013.01.11 Equation of State Calculations by Fast Computing Machines, Metropolis, N. and Rosenbluth, A.W. and Rosenbluth, M.N. and Teller, A.H. and Teller, E., Journal of Chemical Physics, 1953, 1087-1092, 21, shhn001, AIP, 2008.03.24 A ?long indel? model for evolutionary sequence alignment, Miklós, I and Lunter, GA and Holmes, I, mbe, 2004, 3, 529–540, 21, hoehna, SMBE, 2013.08.01 Gates: A graphical notation for mixture models, Minka, T. and Winn, J., 2008, hoehna, Citeseer, 2010.10.21 Ordering and improving the performance of Monte Carlo Markov chains, Mira, A., Statistical Science, 2001, 4, 340–350, 16, MCMC, Convergence, Asymptotic Variance, Speed of Convergence, hoehna, Institute of Mathematical Statistics, 2009.06.01 Ordering Monte Carlo Markov chains, Mira, A. and Geyer, C.J., School of Statistics, University of Minnesota, 1999, Convergence, MCMC, Asymptotic Variance, Speed of Convergence, hoehna, 2009.06.01 The Phylogenetic Study of Adaptive Zones: Has Phytophagy Promoted Insect Diversification?, Mitter, C. and Farrell, B. and Wiegemann, B., an, 132, 107–128, 1988 Nineteen dubious ways to compute the exponential of a matrix, Moler, Cleve and Van Loan, Charles, SIAM review, 1978, 4, 801–836, 20, hoehna, SIAM, 2014.06.23 \textitIndarctos (Ursidae, Mammalia) from the Spanish Turolian (Upper Miocene), Montoya, P and Alcalá, L and Morales, J, Scripta Geologica, 2001, 123–151, 122 Phylogenetic Supertrees, Moore, Brian R and Chan, Kai MA and Donoghue, Michael J, Detecting diversification rate variation in supertrees, 487–533, Springer, 2004, hoehna, 2013.12.14 A Bayesian approach for evaluating the impact of historical events on rates of diversification, Moore, Brian R and Donoghue, Michael J, pnas, 2009, 11, 4307–4312, 106, hoehna, National Acad Sciences, 2013.12.14 Correlates of diversification in the plant clade Dipsacales: geographic movement and evolutionary innovations, Moore, Brian R and Donoghue, Michael J, an, 2007, S2, S28–S55, 170, hoehna, JSTOR, 2013.12.14 Critically evaluating the theory and performance of Bayesian analysis of macroevolutionary mixtures, Moore, Brian R and Höhna, Sebastian and May, Michael R and Rannala, Bruce and Huelsenbeck, John P, pnas, 2016, 34, 9569–9574, 113, hoehna, National Acad Sciences, 2016.10.04 Increasing data transparency and estimating phylogenetic uncertainty in supertrees: approaches using nonparametric bootstrapping, Moore, Brian R and Smith, Stephen A and Donoghue, Michael J, sysbio, 2006, 4, 662–676, 55, hoehna, Oxford 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Divides the set of Taxa in multiple overleafing subsets and recombine them using a supertree algorithm and compared this with common phylogenetic analysis. Only done with MP!, 2008.11.06 Protracted speciation revitalizes the neutral theory of biodiversity, Rosindell, J. and Cornell, S.J. and Hubbell, S.P. and Etienne, R.S., el, 2010, 6, 716–727, 13, hoehna, Wiley Online Library, 2012.03.15 R: A Language and Environment for Statistical Computing, R Core Team, R Foundation for Statistical Computing, Vienna, Austria, 2018, https://www.R-project.org/ RStudio: Integrated Development Environment for R, RStudio Team, RStudio, Inc., Boston, MA, 2015, http://www.rstudio.com/ The bayesian bootstrap, Rubin, D.B., The Annals of Statistics, 1981, 1, 130–134, 9, hoehna, Institute of Mathematical Statistics, 2009.10.13 Simulation and the Monte Carlo Method, Rubinstein, R.Y., John Wiley & Sons, Inc. New York, NY, USA, 1981, shhn001, 2008.09.09 Dealing with Incomplete Taxon Sampling and Diversification of a Large Clade of Mushroom-Forming Fungi, Ryberg, Martin and Matheny, Patrick Brandon, evolution, 2011, 7, 1862–1878, 65, hoehna, Wiley Online Library, 2015.09.17 DivBayes and SubT: exploring species diversification using Bayesian statistics, Ryberg, Martin and Nilsson, R Henrik and Matheny, P Brandon, bi, 2011, 17, 2439–2440, 27, hoehna, Oxford Univ Press, 2015.08.24 Markov chain Monte Carlo computation of confidence intervals for substitution-rate variation in proteins, Rzhetsky, A. and Morozov, P., Pac Symp Biocomput, 2001, 203–214, 6, shhn001, 2008.12.02 Positive natural selection in the human lineage, Sabeti, PC and Schaffner, SF and Fry, B and Lohmueller, J and Varilly, P and Shamovsky, O and Palma, A and Mikkelsen, TS and Altshuler, D and Lander, ES, Science, 2006, 5780, 1614–1620, 312, hoehna, American Association for the Advancement of Science, 2013.08.10 Relative Efficiencies of the Fitch-Margoliash, Maximum-Parsimony, Maximum-Likelihood, Minimum-Evolution, and Neighbor-joining Methods of Phylogenetic Tree Construction in Obtaining the Correct Tree, Saitou, N and Imanishi, T, mbe, 1989, 5, 514-525, 6, http://mbe.oxfordjournals.org/cgi/reprint/6/5/514.pdf, shhn001, 2008.04.02 Phylogenetic supertrees: Assembling the trees of life, Sanderson, M.J. and Purvis, A. and Henze, C., tee, 1998, 3, 105–109, 13, shhn001, Elsevier, 2008.09.16 10.1093/bioinformatics/19.2.301 phangorn: phylogenetic analysis in R, Schliep, K.P., Bioinformatics, 2011, 27, 4, 592–593, https://doi.org/10.1093/bioinformatics/btq706 10.1111/2041-210X.12760 The ecology of adaptive radiation, Schluter, D., Oxford University Press, USA, 2000, hoehna, 2012.08.01 Estimates of positive Darwinian selection are inflated by errors in sequencing, annotation, and alignment, Schneider, Adrian and Souvorov, Alexander and Sabath, Niv and Landan, Giddy and Gonnet, Gaston H and Graur, Dan, Genome biology and evolution, 2009, 114, 1, hoehna, Oxford University Press, 2013.08.10 Multiple alignment by sequence annealing, Schwartz, Ariel S and Pachter, Lior, bi, 2007, 2, e24–e29, 23, hoehna, Oxford Univ Press, 2013.08.05 Estimating the dimension of a model, Schwarz, Gideon, The annals of statistics, 1978, 2, 461–464, 6, hoehna, Institute of Mathematical Statistics, 2013.04.23 The Physics of Networks, Seary, A. and Richards, W., INSNA Sunbelt XVII, San Diego, February, 1997, 13–17, shhn001, 2009.02.04 Fossil evidence for an ancient divergence of lorises and galagos, Seiffert, Erik R and Simons, Elwyn L and Attia, Yousry, Nature, 2003, 6930, 421–424, 422, hoehna, Nature Publishing Group, 2015.07.30 DOI: 10.1016/S0166-218X(00)00202-X Choosing appropriate substitution models for the phylogenetic analysis of protein-coding sequences, Shapiro, B. and Rambaut, A. and Drummond, A.J., mbe, 2006, 1, 7, 23, hoehna, SMBE, 2010.03.15 shiny: Web Application Framework for R, Chang, Winston and Cheng, Joe and Allaire, JJ and Xie, Yihui and McPherson, Jonathan, 2018, R package version 1.1.0, https://CRAN.R-project.org/package=shiny PyRate: a new program to estimate speciation and extinction rates from incomplete fossil data, Silvestro, Daniele and Salamin, Nicolas and Schnitzler, Jan, mee, 2014, 10, 1126–1131, 5, hoehna, Wiley Online Library, 2015.09.22 Bayesian estimation of speciation and extinction from incomplete fossil occurrence data, Silvestro, Daniele and Schnitzler, Jan and Liow, Lee Hsiang and Antonelli, Alexandre and Salamin, Nicolas, sysbio, 2014, 3, 349–367, 63, hoehna, Oxford University Press, 2015.08.24 A Bayesian framework to estimate diversification rates and their variation through time and space, Silvestro, D. and Schnitzler, J. and Zizka, G., bmcevobio, 2011, 1, 311, 11, hoehna, BioMed Central Ltd, 2012.07.31 How meaningful are Bayesian support values?, Simmons, M.P. and Pickett, K.M. and Miya, M., mbe, 2004, 1, 188, 21, hoehna, SMBE, 2011.09.14 10.1093/sysbio/syt066 Diversity versus disparity and the radiation of modern cetaceans, Slater, Graham J and Price, Samantha A and Santini, Francesco and Alfaro, Michael E, procb, 2010, 1697, 3097–3104, 277, hoehna, The Royal Society, 2014.03.12 Integrating fossils with molecular phylogenies improves inference of trait evolution, Slater, Graham J and Harmon, Luke J and Alfaro, Michael E, Evolution: International Journal of Organic Evolution, 66, 12, 3931–3944, 2012, Wiley Online Library Bayesian computation via the Gibbs sampler and related Markov chain Monte Carlo methods, Smith, AFM and Roberts, GO, Journal of the Royal Statistical Society. Series B (Methodological), 1993, 1, 3–23, 55, 0035-9246, Hoehna, JSTOR, 2011.03.03 boa: An R package for MCMC output convergence assessment and posterior inference, Smith, B.J., Journal of Statistical Software, 2007, 11, 1–37, 21, Hoehna, American Statistical Association, 2010.12.13 Bayesian output analysis program, Smith, B., 2004, Hoehna, The University of Iowa College of Public Health, Iowa City, 2011.02.08 Numerical taxonomy, Sneath, P.H.A. and Sokal, R.R., Springer, 1973, shhn001, 2009.02.23 Solving differential equations in R: Package deSolve, Soetaert, K. and Petzoldt, T. and Setzer, R.W., Journal of Statistical Software, 2010, 9, 1–25, 33, hoehna, 2013.01.30 Patterns of mammalian diversification in recent evolutionary times: global tendencies and methodological issues, Soria-Carrasco, V. and Castresana, J., Journal of Evolutionary Biology, 2011, 12, 2611?-2623, 24, hoehna, Wiley Online Library, 2012.07.27 Sequential updating of conditional probabilities on directed graphical structures, Spiegelhalter, David J and Lauritzen, Steffen L, Networks, 1990, 5, 579–605, 20, hoehna, Wiley Online Library, 2013.05.31 Macroevolutionary dynamics and historical biogeography of primate diversification inferred from a species supermatrix, Springer, Mark S and Meredith, Robert W and Gatesy, John and Emerling, Christopher A and Park, Jong and Rabosky, Daniel L and Stadler, Tanja and Steiner, Cynthia and Ryder, Oliver A and Janečka, Jan E and others, pone, 2012, 11, e49521, 7, hoehna, Public Library of Science, 2016.02.22 Placental mammal diversification and the Cretaceous–Tertiary boundary, Springer, Mark S and Murphy, William J and Eizirik, Eduardo and O’Brien, Stephen J, pnas, 2003, 3, 1056–1061, 100, hoehna, National Acad Sciences, 2013.09.09 How can we improve accuracy of macroevolutionary rate estimates?, Stadler, Tanja, sysbio, 2013, 2, 321–329, 62, hoehna, Oxford University Press, 2013.09.10 Mammalian phylogeny reveals recent diversification rate shifts, Stadler, T., pnas, 2011, 15, 6187–6192, 108, hoehna, National Acad Sciences, 2012.07.27 Simulating trees with a fixed number of extant species, Stadler, Tanja, sysbio, 2011, 5, 676-684, 60, hoehna, Oxford University Press, 2014.09.19 Sampling-through-time in birth-death trees, Stadler, T., jtb, 2010, 3, 396–404, 267, Hoehna, Elsevier, 2010.10.10 TreeSim: Simulating trees under the birth-death model, Stadler, Tanja, R package version 1.0, 2010, Hoehna, 2010.09.02, http://CRAN.R-project.org/package=TreeSim On incomplete sampling under birth-death models and connections to the sampling-based coalescent, Stadler, Tanja, jtb, 2009, 1, 58–66, 261, Birth-death trees, hoehna, Elsevier, 2009.08.03 Estimating Speciation and Extinction Rates for Phylogenies of Higher Taxa, Stadler, Tanja and Bokma, Folmer, sysbio, 2013, 2, 220–230, 62, hoehna, Oxford University Press, 2013.04.17 A polynomial time algorithm for calculating the probability of a ranked gene tree given a species tree, Stadler, Tanja and Degnan, James H, Algorithms for Molecular Biology, 2012, 1, 7, 7, hoehna, BioMed Central Ltd, 2013.06.11 Birth-death skyline plot reveals temporal changes of epidemic spread in HIV and hepatitis C virus (HCV), Stadler, Tanja and Kühnert, Denise and Bonhoeffer, Sebastian and Drummond, Alexei J, pnas, 2013, 1, 228–233, 110, hoehna, National Acad Sciences, 2014.03.09 Dating phylogenies with sequentially sampled tips, Stadler, Tanja and Yang, Ziheng, sysbio, 2013, 5, 674–688, 62, hoehna, Oxford University Press, 2015.10.22 Distributions of Tree Comparison Metrics-Some New Results, Steel, Mike A. and Penny, David, sysbio, 1993, 126-141, 42, June, 2, 126-141, 42 The Bayesian" star paradox" persists for long finite sequences, Steel, M. and Matsen, F.A., mbe, 2007, 4, 1075, 24, hoehna, SMBE, 2009.12.15 Parsimony, Likelihood, and the Role of Models in Molecular Phylogenetics, Steel, Mike and Penny, David, mbe, 2000, 6, 839-850, 17, Methods such as maximum parsimony (MP) are frequently criticized as being statistically unsound and not being based on any "model." On the other hand, advocates of MP claim that maximum likelihood (ML) has some fundamental problems. Here, we explore the connection between the different versions of MP and ML methods, particularly in light of recent theoretical results. We describe links between the two methods–for example, we describe how MP can be regarded as an ML method when there is no common mechanism between sites (such as might occur with morphological data and certain forms of molecular data). In the process, we clarify certain historical points of disagreement between proponents of the two methodologies, including a discussion of several forms of the ML optimality criterion. We also describe some additional results that shed light on how much needs to be assumed about underling models of sequence evolution in order to successfully reconstruct evolutionary trees., http://mbe.oxfordjournals.org/cgi/reprint/17/6/839.pdf, shhn001, 2008.04.02 Radiation of extant cetaceans driven by restructuring of the oceans, Steeman, Mette E and Hebsgaard, Martin B and Fordyce, R Ewan and Ho, Simon YW and Rabosky, Daniel L and Nielsen, Rasmus and Rahbek, Carsten and Glenner, Henrik and Sørensen, Martin V and Willerslev, Eske, sysbio, 2009, 6, 573–585, 58, hoehna, Oxford University Press, 2013.05.08 Genomic data support the hominoid slowdown and an Early Oligocene estimate for the hominoid–cercopithecoid divergence, Steiper, Michael E and Young, Nathan M and Sukarna, Tika Y, pnas, 2004, 49, 17021–17026, 101, hoehna, National Acad Sciences, 2015.07.30 Estimation of statistical errors in molecular simulation calculations, Straatsma, TP and Berendsen, HJC and Stam, AJ, Molecular Physics, 1986, 1, 89–95, 57, hoehna, Taylor & Francis, 2011.07.19 Bayesian Probabilities and Quartet Puzzling, Strimmer, K and Goldman, N and von Haeseler, A, mbe, 1997, 2, 210-211, 14, http://mbe.oxfordjournals.org/cgi/reprint/14/2/210.pdf, shhn001, 2008.11.18 Quartet Puzzling: A Quartet Maximum-Likelihood Method for Reconstructing Tree Topologies, Strimmer, K. and von Haeseler, A., mbe, 1996, 7, 964, 13, shhn001, SMBE, 2008.11.18 BAli-Phy: simultaneous Bayesian inference of alignment and phylogeny, Suchard, Marc A and Redelings, Benjamin D, bi, 2006, 16, 2047–2048, 22, hoehna, Oxford Univ Press, 2015.02.24 Bayesian Selection of Continuous-Time Markov Chain Evolutionary Models, Suchard, Marc A and Weiss, Robert E and Sinsheimer, Janet S, mbe, 2001, 6, 1001–1013, 18, hoehna, SMBE, 2013.03.26 Models for estimating Bayes factors with applications to phylogeny and tests of monophyly, Suchard, M.A. and Weiss, R.E. and Sinsheimer, J.S., Biometrics, 2005, 3, 665–673, 61, hoehna, Wiley Online Library, 2011.09.14 DendroPy: a Python library for phylogenetic computing, Sukumaran, Jeet and Holder, Mark T, bi, 2010, 12, 1569–1571, 26, hoehna, Oxford Univ Press, 2013.05.06 Model selection in phylogenetics, Sullivan, Jack and Joyce, Paul, arees, 2005, 445–466, 36, hoehna, JSTOR, 2013.04.19 Fundamental differences between the methods of maximum likelihood and maximum posterior probability in phylogenetics, Svennblad, B. and Erixon, P. and Oxelman, B. and Britton, T., sysbio, 2006, 1, 116, 55, hoehna, 2009.10.13 10.1103/PhysRevLett.58.86 When are phylogeny estimates from molecular and morphological data incongruent, Swofford, D.L., Phylogenetic Analysis of DNA Sequences, 1991, 295–333, shhn001, Oxford University Press, 2007.09.26 Phylogenetic inference, Swofford, D.L. and Olsen, G.J. and Waddell, P.J. and Hillis, D.M., Molecular Systematics, 1996, 407–514, 2, shhn001, Sunderland, 2008.11.18 Phylogenetic modeling of lateral gene transfer reconstructs the pattern and relative timing of speciations, Szöllősi, Gergely J and Boussau, Bastien and Abby, Sophie S and Tannier, Eric and Daubin, Vincent, pnas, 2012, 43, 17513–17518, 109, hoehna, National Acad Sciences, 2015.05.19 10.1093/sysbio/syu048 Estimation of the number of nucleotide substitutions when there are strong transition-transversion and G+ C-content biases., Tamura, Koichiro, mbe, 1992, 4, 678–687, 9, hoehna, SMBE, 2013.07.16 Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees, Tamura, K and Nei, M, mbe, 1993, 3, 512-526, 10, http://mbe.oxfordjournals.org/cgi/reprint/10/3/512.pdf, shhn001, 2008.12.02 Sequence context affects the rate of short insertions and deletions in flies and primates, Tanay, Amos and Siggia, Eric D, Genome biology, 2008, 2, R37, 9, hoehna, BioMed Central Ltd, 2013.08.01 A recursive approach to low complexity codes, Tanner, R, Information Theory, IEEE Transactions on, 1981, 5, 533–547, 27, hoehna, IEEE, 2013.12.03 Some Probabilistic and Statistical Problems in the Analysis of DNA Sequences, Tavaré, S., Some Mathematical Questions in Biology: DNA Sequence Analysis, 1986, 57–86, 17, shhn001, 2009.02.05 Using the fossil record to estimate the age of the last common ancestor of extant primates, Tavaré, Simon and Marshall, Charles R and Will, Oliver and Soligo, Christophe and Martin, Robert D, Nature, 2002, 6882, 726–729, 416, hoehna, Nature Publishing Group, 2015.07.30 10.1093/molbev/msh156 DOI: 10.1016/j.meegid.2004.07.001 R: A language and environment for statistical computing, Team, R Core and others, 2012, hoehna, R Foundation for Statistical Computing, Vienna, Austria. ISBN, 2014.11.28 Human evolutionary trees, Thompson, E.A., Cambridge University Press Cambridge, 1975, hoehna, Some stuff about the Birth Death process, 2009.07.29 A comparison of methods for computing autocorrelation time, Thompson, M.B., Department of Statistics, University of Toronto, 2010, Arxiv preprint arXiv:1011.0175, hoehna, 2011.07.12 A critical appraisal of the use of microRNA data in phylogenetics, Thomson, Robert C and Plachetzki, David C and Mahler, D Luke and Moore, Brian R, pnas, 2014, 35, E3659–E3668, 111, hoehna, National Acad Sciences, 2015.08.13 Estimating the rate of evolution of the rate of molecular evolution, Thorne, J. and Kishino, H. and Painter, I. S., mbe, 1998, 1647–1657, 15, hoehna, 2013.08.01 Divergence time and evolutionary rate estimation with multilocus data, Thorne, Jeffrey L and Kishino, Hirohisa, sysbio, 2002, 5, 689–702, 51, hoehna, Oxford University Press, 2014.06.04 Inching toward reality: an improved likelihood model of sequence evolution, Thorne, Jeffrey L and Kishino, Hirohisa and Felsenstein, Joseph, jme, 1992, 1, 3–16, 34, hoehna, Springer, 2013.06.28 An evolutionary model for maximum likelihood alignment of DNA sequences, Thorne, Jeffrey L and Kishino, Hirohisa and Felsenstein, Joseph, jme, 1991, 2, 114–124, 33, hoehna, Springer, 2013.06.28 The Molecular Clock Hypothesis: Biochemical Evolution, Genetic Differentiation and Systematics, Thorpe, J P, Annual Review of Ecology and Systematics, 1982, 1, 139-168, 13, http://arjournals.annualreviews.org/doi/pdf/10.1146/annurev.es.13.110182.001035, shhn001, 2008.04.07 A Note on Metropolis-Hastings Kernels for General State Spaces, Tierney, Luke, The Annals of Applied Probability, 1998, 1, 1–9, 8, The Metropolis-Hastings algorithm is a method of constructing a reversible Markov transition kernel with a specified invariant distribution. This note describes necessary and sufficient conditions on the candidate generation kernel and the acceptance probability function for the resulting transition kernel and invariant distribution to satisfy the detailed balance conditions. A simple general formulation is used that covers a range of special cases treated separately in the literature. In addition, results on a useful partial ordering of finite state space reversible transition kernels are extended to general state spaces and used to compare the performance of two approaches to using mixtures in Metropolis-Hastings kernels., Copyright ? 1998 Institute of Mathematical Statistics, 10505164, primary_article, Feb., 1998, hoehna, Institute of Mathematical Statistics, 2009.07.20 Markov Chains for Exploring Posterior Distributions, Tierney, Luke, The Annals of Statistics, 1994, 4, 1701–1728, 22, Several Markov chain methods are available for sampling from a posterior distribution. Two important examples are the Gibbs sampler and the Metropolis algorithm. In addition, several strategies are available for constructing hybrid algorithms. This paper outlines some of the basic methods and strategies and discusses some related theoretical and practical issues. On the theoretical side, results from the theory of general state space Markov chains can be used to obtain convergence rates, laws of large numbers and central limit theorems for estimates obtained from Markov chain methods. These theoretical results can be used to guide the construction of more efficient algorithms. For the practical use of Markov chain methods, standard simulation methodology provides several variance reduction techniques and also give guidance on the choice of sample size and allocation., Copyright © 1994 Institute of Mathematical Statistics, 00905364, primary_article, Dec., 1994, shhn001, Institute of Mathematical Statistics, 2008.04.11 Some Adaptive Monte Carlo Methods for Bayesian Inference, Tierney, L. and Mira, A., Statistics in Medicine, 1999, 1718, 2507–2515, 18, shhn001, 2008.09.09 Phylogenetic incongruence between nuclear and mitochondrial markers in the Asian colobines and the evolution of the langurs and leaf monkeys, Ting, Nelson and Tosi, Anthony J and Li, Ying and Zhang, Ya-Ping and Disotell, Todd R, mpe, 2008, 2, 466–474, 46, hoehna, Elsevier, 2015.07.30 Large-scale phylogeny of chameleons suggests African origins and Eocene diversification, Tolley, Krystal A and Townsend, Ted M and Vences, Miguel, procb, 2013, 1759, 280, hoehna, The Royal Society, 2013.05.28 X-chromosomal window into the evolutionary history of the guenons (Primates: Cercopithecini), Tosi, Anthony J and Detwiler, Kate M and Disotell, Todd R, mpe, 2005, 1, 58–66, 36, hoehna, Elsevier, 2015.07.30 Ecological limits to plant phenotypic plasticity, Valladares, F. and Gianoli, E. and Gómez, J.M., New Phytologist, 2007, 4, 749–763, 176, hoehna, Wiley Online Library, 2012.03.15 Efficient Bayesian inference under the structured coalescent, Vaughan, Timothy G and Kühnert, Denise and Popinga, Alex and Welch, David and Drummond, Alexei J, bi, 2014, 16, 2272?-2279, 30, hoehna, Oxford Univ Press, 2015.05.19 Geology and palaeontology of the Upper Miocene Toros-Menalla hominid locality, Chad, Vignaud, Patrick and Duringer, Philippe and Mackaye, Hassane Taı̈sso and Likius, Andossa and Blondel, Cécile and Boisserie, Jean-Renaud and de Bonis, Louis and Eisenmann, Véra and Etienne, Marie-Esther and Geraads, Denis and others, Nature, 2002, 6894, 152–155, 418, hoehna, Nature Publishing Group, 2015.07.30 Heterostyly accelerates diversification via reduced extinction in primroses, de Vos, Jurriaan M and Hughes, Colin E and Schneeweiss, Gerald M and Moore, Brian R and Conti, Elena, Proceedings of the Royal Society of London B: Biological Sciences, 2014, 1784, 20140075, 281, hoehna, The Royal Society, 2015.08.13 A New Dated Supertree of the Primates, Vos, R.A. and Mooers, A.Ø., Simon Fraser University, 2006 Reconstructing divergence times for supertrees, Vos, R.A. and Mooers, A.Ø. and Bininda-Emonds, ORP, Phylogenetic supertrees: Combining information to reveal the tree of life, 2004, 281–299, shhn001, 2008.11.06 Very Fast Algorithms for Evaluating the Stability of ML and Bayesian Phylogenetic Trees from Sequence Data, Waddell, P.J. and Kishino, H. and Ota, R., Genome Informatics, 2002, 82–92, 13, hoehna, 2009.10.13 10.1016/0378-4371(90)90275-W Calibration uncertainty in molecular dating analyses: there is no substitute for the prior evaluation of time priors, Warnock, Rachel CM and Parham, James F and Joyce, Walter G and Lyson, Tyler R and Donoghue, Philip CJ, procb, 2015, 1798, 20141013, 282, hoehna, The Royal Society, 2015.09.08 Exploring uncertainty in the calibration of the molecular clock, Warnock, Rachel CM and Yang, Ziheng and Donoghue, Philip CJ, Biology letters, 2012, 1, 156–159, 8, hoehna, The Royal Society, 2014.01.25 rwty: R We There Yet, Warren, DL and Geneva, A and Swofford, DL and Lanfear, R, A package for visualizing MCMC convergence in phylogenetics, 2016 On the similarity of dendrograms, Waterman, MS and Smith, TF, jtb, 1978, 789-800, 732, 73, shhn001, 2009.01.24 Historical biogeography inference in Malesia, Webb, Campbell O and Ree, RH, Biotic evolution and environmental change in Southeast Asia, 2012, 191–215, Cambridge University Press Cambridge Critiquing blind dating: the dangers of over-confident date estimates in comparative genomics, Wheat, Christopher W and Wahlberg, Niklas, tee, 2013, 11, 636–642, 28, hoehna, Elsevier, 2015.09.08 Distinctions between optimal and expected support, Wheeler, W.C., Cladistics, 2010, 657?663, 26, hoehna, Wiley Online Library, 2011.09.14 10.1093/molbev/msm274 Cretaceous eutherians and Laurasian origin for placental mammals near the K/T boundary, Wible, JR and Rougier, GW and Novacek, MJ and Asher, RJ, Nature, 2007, 7147, 1003–1006, 447, hoehna, Nature Publishing Group, 2013.09.10 dplyr: A Grammar of Data Manipulation, Wickham, Hadley and François, Romain and Henry, Lionel and Müller, Kirill, 2018, R package version 0.7.6, https://CRAN.R-project.org/package=dplyr Inferences from DNA data: population histories, evolutionary processes and forensic match probabilities, Wilson, I.J. and Weale, M.E. and Balding, D.J., Journal of the Royal Statistical Society: Series A (Statistics in Society), 2003, 155–188, 166, shhn001, Blackwell Synergy, paper about BATWING, 2008.05.16 Genealogical Inference From Microsatellite Data, Wilson, Ian J. and Balding, David J., genetics, 1998, 499-510, 150, Ease and accuracy of typing, together with high levels of polymorphism and widespread distribution in the genome, make microsatellite (or short tandem repeat) loci an attractive potential source of information about both population histories and evolutionary processes. However, microsatellite data are difficult to interpret, in particular because of the frequency of back-mutations. Stochastic models for the underlying genetic processes can be specified, but in the past they have been too complicated for direct analysis. Recent developments in stochastic simulation methodology now allow direct inference about both historical events, such as genealogical coalescence times, and evolutionary parameters, such as mutation rates. A feature of the Markov chain Monte Carlo (MCMC) algorithm that we propose here is that the likelihood computations are simplified by treating the (unknown) ancestral allelic states as auxiliary parameters. We illustrate the algorithm by analyzing microsatellite samples simulated under the model. Our results suggest that a single microsatellite usually does not provide enough information for useful inferences, but that several completely linked microsatellites can be informative about some aspects of genealogical history and evolutionary processes. We also reanalyze data from a previously published human Y chromosome microsatellite study, finding evidence for an effective population size for human Y chromosomes in the low thousands and a recent time since their most recent common ancestor: the 95% interval runs from 15,000 to 130,000 years, with most likely values around 30,000 years., http://www.genetics.org/cgi/reprint/150/1/499.pdf, shhn001, paper which proposes our wilson-balding operator., 2007.10.01 Alignment uncertainty and genomic analysis, Wong, Karen M and Suchard, Marc A and Huelsenbeck, John P, Science, 2008, 5862, 473–476, 319, hoehna, American Association for the Advancement of Science, 2013.07.30 Bayesian analysis using a simple likelihood model outperforms parsimony for estimation of phylogeny from discrete morphological data, Wright, April M and Hillis, David M, PLoS One, 9, 10, e109210, 2014, Public Library of Science Modeling Character Change Heterogeneity in Phylogenetic Analyses of Morphology through the Use of Priors, Wright, April M. and Lloyd, Graeme T. and Hillis, David M., sysbio, 2016, 4, 602-611, 65 Accounting for alignment uncertainty in phylogenomics, Wu, Martin and Chatterji, Sourav and Eisen, Jonathan A, pone, 2012, 1, e30288, 7, hoehna, Public Library of Science, 2013.08.10 Improving Marginal Likelihood Estimation for Bayesian Phylogenetic Model Selection, Xie, W. and Lewis, P.O. and Fan, Y. and Kuo, L. and Chen, M.H., sysbio, 2011, 2, 150–160, 60, hoehna, Oxford University Press, 2013.01.24 Molecular Evolution: A Statistical Approach, Yang, Ziheng, Oxford University Press, 2014, hoehna, 2015.03.31 Empirical evaluation of a prior for Bayesian phylogenetic inference, Yang, Z., Phil. Trans. R. Soc. B, 2008, 4031–4039, 363, hoehna, Citeseer, 2009.12.15 10.1093/molbev/msm088 Fair-balance paradox, star-tree paradox, and Bayesian phylogenetics, Yang, Z., mbe, 2007, 8, 1639, 24, hoehna, SMBE, 2009.12.15 Computational molecular evolution, Yang, Ziheng, Oxford University Press Oxford, 2006, 284, hoehna, 2014.06.23 Inference of selection from multiple species alignments, Yang, Ziheng, Current opinion in genetics & development, 2002, 6, 688–694, 12, hoehna, Elsevier, 2013.08.10 10.1093/bioinformatics/13.5.555 Among-site rate variation and its impact on phylogenetic analyses, Yang, Ziheng, tee, 1996, 9, 367–372, 11, hoehna, Elsevier, 2013.05.20 Estimating the pattern of nucleotide substitution, Yang, Ziheng, jme, 1994, 1, 105–111, 39, hoehna, Springer, 2013.05.20 Maximum Likelihood Phylogenetic Estimation from DNA Sequences with Variable Rates Over Sites: Approximate Methods, Yang, Ziheng, jme, 1994, 3, 306–314, 39, hoehna, Springer, 2013.10.10 Statistical methods for detecting molecular adaptation, Yang, Ziheng and Bielawski, Joseph P, tee, 2000, 12, 496–503, 15, hoehna, Elsevier, 2013.08.10 Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages, Yang, Ziheng and Nielsen, Rasmus, mbe, 2002, 6, 908–917, 19, hoehna, SMBE, 2013.08.10 Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models, Yang, Ziheng and Nielsen, Rasmus, mbe, 2000, 1, 32–43, 17, hoehna, SMBE, 2013.08.10 Synonymous and nonsynonymous rate variation in nuclear genes of mammals, Yang, Ziheng and Nielsen, Rasmus, jme, 1998, 4, 409–418, 46, hoehna, Springer, 2013.08.10 Codon-substitution models for heterogeneous selection pressure at amino acid sites, Yang, Ziheng and Nielsen, Rasmus and Goldman, Nick and Pedersen, Anne-Mette Krabbe, genetics, 2000, 1, 431–449, 155, hoehna, Genetics Soc America, 2013.08.10 Molecular phylogenetics: principles and practice, Yang, Ziheng and Rannala, Bruce, Nature Reviews Genetics, 2012, 5, 303–314, 13, hoehna, Nature Publishing Group, 2013.04.19 10.1093/molbev/msj024 Branch-length prior influences Bayesian posterior probability of phylogeny, Yang, Z. and Rannala, B., sysbio, 2005, 3, 455, 54, hoehna, 2009.12.15 Bayesian phylogenetic inference using DNA sequences: a Markov Chain Monte Carlo Method, Yang, Z and Rannala, B, mbe, 1997, 7, 717-724, 14, http://mbe.oxfordjournals.org/cgi/reprint/14/7/717.pdf, shhn001, Yang and Rannala describe here their PAML (Phylogenetic Analysis by Maximum Likelihood) application. They used a simple NNI for rooted trees, 2008.03.24 Statistical properties of the branch-site test of positive selection, Yang, Ziheng and dos Reis, Mario, mbe, 2011, 3, 1217–1228, 28, hoehna, SMBE, 2013.08.10 On the use of nucleic acid sequences to infer early branchings in the tree of life., Yang, Ziheng and Roberts, Dave, Molecular Biology and Evolution, 1995, 3, 451–458, 12, hoehna, SMBE, 2015.06.18 Searching for efficient Markov chain Monte Carlo proposal kernels, Yang, Ziheng and Rodrı́guez, Carlos E, pnas, 2013, 48, 19307–19312, 110, hoehna, National Acad Sciences, 2014.10.04 Codon-substitution models to detect adaptive evolution that account for heterogeneous selective pressures among site classes, Yang, Ziheng and Swanson, Willie J, mbe, 2002, 1, 49–57, 19, hoehna, SMBE, 2013.08.10 Bayes empirical Bayes inference of amino acid sites under positive selection, Yang, Ziheng and Wong, Wendy SW and Nielsen, Rasmus, mbe, 2005, 4, 1107–1118, 22, hoehna, SMBE, 2013.08.10 Comparison of likelihood and Bayesian methods for estimating divergence times using multiple gene loci and calibration points, with application to a radiation of cute-looking mouse lemur species, Yang, Ziheng and Yoder, Anne D, sysbio, 2003, 5, 705–716, 52, hoehna, Oxford University Press, 2014.06.05 A mathematical theory of evolution, based on the conclusions of Dr. JC Willis, FRS, Yule, G.U., Philosophical Transactions of the Royal Society of London. Series B, Containing Papers of a Biological Character, 1925, 21–87, 213, hoehna, JSTOR, 2012.07.24 Robustness of Compound Dirichlet Priors for Bayesian Inference of Branch Lengths, Zhang, Chi and Rannala, Bruce and Yang, Ziheng, sysbio, 2012, 5, 779–784, 61, hoehna, Oxford University Press, 2016.08.01 10.1093/sysbio/syv080 Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level, Zhang, Jianzhi and Nielsen, Rasmus and Yang, Ziheng, mbe, 2005, 12, 2472–2479, 22, hoehna, SMBE, 2013.08.10 Molecular disease, evolution, and genetic heterogeneity, Zuckerkandl, E. and Pauling, L., Horizons in Biochemistry, 1962, Kasha, M. and Pullman, B., 189–225, Academic Press, New York 2017-05-10T06:19:58.000+0200, Zuckerkandl, Emile and Pauling, Linus, https://www.bibsonomy.org/bibtex/26329d52a5aeb13d51764babe8246cedd/salotz, 1ba5cccd57b257ef262e57060ddf2b24, 6329d52a5aeb13d51764babe8246cedd, Evolving genes and proteins, evolution pauling protein-evolution, 97–166, 2017-05-10T06:19:58.000+0200, Evolutionary divergence and convergence in proteins, 97, 1965 Increased taxon sampling greatly reduces phylogenetic error, Zwickl, Derrick J and Hillis, David M, sysbio, 2002, 4, 588–598, 51, hoehna, Oxford University Press, 2013.05.08 Model parameterization, prior distributions, and the general time-reversible model in Bayesian phylogenetics, Zwickl, Derrick J and Holder, Mark T, sysbio, 2004, 6, 877–888, 53, hoehna, Oxford University Press, 2015.01.19 Magnuson-Ford, Karen and Otto, Sarah P, Linking the Investigations of Character Evolution and Species Diversification, an, 2012, 180, 2, 225–245, University of Chicago Press Chicago, IL Beaulieu, Jeremy M and O’Meara, Brian C, Detecting hidden diversification shifts in models of trait-dependent speciation and extinction, sysbio, 2016, 65, 4, 583–601, hoehna, Oxford University Press, 2016.10.12 The fossilized birth-death model for the analysis of stratigraphic range data under different speciation concepts, Stadler, Tanja and Gavryushkina, Alexandra and Warnock, Rachel and Drummond, Alexei J and Heath, Tracy A, arXiv preprint arXiv:1706.10106, 2017 Phillips, Aloysius J., Homology assessment and molecular sequence alignment, Journal of Biomedical Informatics, 2006, 39, 1, 18 - 33, 1532-0464, Phylogenetic Inferencing: Beyond Biology Freudenstein, John V., Characters, States and Homology, Systematic Biology, 2005, 54, 6, 965 Wright, April M and Hillis, David M, Bayesian analysis using a simple likelihood model outperforms parsimony for estimation of phylogeny from discrete morphological data, PLoS One, 2014, 9, 10, e109210, Public Library of Science Allman, E. S. and Rhodes, J. A., Identifying evolutionary trees and substitution parameters for the general Markov model with invariable sites, Mathematical Biosciences, 2008, 211, 18–33 Tuffley, C. and Steel, M., Modeling the covarion hypothesis of nucleotide substitution, Mathematical Biosciences, 1998, 147, 63–91 Beaulieu, Jeremy M and O’Meara, Brian C and Donoghue, Michael J, Identifying hidden rate changes in the evolution of a binary morphological character: the evolution of plant habit in campanulid angiosperms, sysbio, 2013, 62, 5, 725–737, Oxford University Press Pagel, Mark, Detecting correlated evolution on phylogenies: a general method for the comparative analysis of discrete characters, Proceedings of the Royal Society of London B: Biological Sciences, 1994, 255, 1342, 37–45, The Royal Society Lartillot, N. and Philippe, H., A Bayesian mixture model for across-site heterogeneities in the amino-acid replacement process, Molecular Biology and Evolution, 2004, 21, 1095–1109 10.1111/evo.13117 10.1093/bioinformatics/btx155 10.7287/peerj.preprints.2579v1 Lartillot, N. and Philippe, H., A Bayesian mixture model for across-site heterogeneities in the amino-acid replacement process, Molecular Biology and Evolution, 2004, 21, 1095–1109 10.1111/evo.13117 10.1093/bioinformatics/btx155 10.7287/peerj.preprints.2579v1 Evolution and the nature of science: On the historical discord and its implications for education, Rudolph, John L and Stewart, Jim, Journal of Research in Science Teaching: The Official Journal of the National Association for Research in Science Teaching, 35, 10, 1069–1089, 1998, Wiley Online Library Tree thinking cannot taken for granted: challenges for teaching phylogenetics, Sandvik, Hanno, Theory in Biosciences, 127, 1, 45–51, 2008, Springer Population thinking and tree thinking in systematics, O’Hara, Robert J, Zoologica scripta, 26, 4, 323–329, 1997, Wiley Online Library 10.1007/s12052-010-0254-9 10.1662/0002-7685(2007)69[71:CSMAET]2.0.CO;2

' -V authors='

April Wright http://orcid.org/0000-0003-4692-3225

' -V month=01 -V day=16 -V year=2019 -V issue=11 -V volume=2 -V page=35 -V title='treesiftr: An R package and server for viewing phylogenetic trees and data' -f markdown paper.md -o 10.21105.jose.00035.crossref.xml --template /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/resources/crossref.template from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/processor.rb:225:in generate_crossref' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/lib/whedon/processor.rb:91:incompile' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/bin/whedon:76:in compile' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/command.rb:27:inrun' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/invocation.rb:126:in invoke_command' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor.rb:387:indispatch' from /app/vendor/bundle/ruby/2.4.0/gems/thor-0.20.0/lib/thor/base.rb:466:in start' from /app/vendor/bundle/ruby/2.4.0/bundler/gems/whedon-50d5912cf72a/bin/whedon:113:in<top (required)>' from /app/vendor/bundle/ruby/2.4.0/bin/whedon:23:in load' from /app/vendor/bundle/ruby/2.4.0/bin/whedon:23:in

'

labarba commented 5 years ago

😱

wrightaprilm commented 5 years ago

That was surprising! Not even a little bit what I expected to occur.

I added back in the string expansion block. There were two of them. It's compiling on local via R's Knitr machinery.

labarba commented 5 years ago

@whedon generate pdf

whedon commented 5 years ago

Attempting PDF compilation. Reticulating splines etc...

whedon commented 5 years ago

:point_right: Check article proof :page_facing_up: :point_left:

labarba commented 5 years ago

It compiles that way ... I notice that two references bleed out of the right margin (long DOIs). Can you think of any way to fix that? @arfon, we may still need your help here, sorry!

wrightaprilm commented 5 years ago

It's such an odd format for a DOI. I also see a render issue in the references on a hyphenated first name. I'll wait to push my fix until I hear back on this issue.

arfon commented 5 years ago

It compiles that way ... I notice that two references bleed out of the right margin (long DOIs). Can you think of any way to fix that? @arfon, we may still need your help here, sorry!

Lemme see what I can do. I think https://github.com/openjournals/whedon/pull/39 might fix this.

arfon commented 5 years ago

Unfortunately this is a non-trivial fix. I can fix one of the DOI strings but the longer one is going to require some work. @labarba - it's up to you how we proceed from here, i.e. we could wait to see if we can get this fixed or accept now and update the paper later when we have a fix.

labarba commented 5 years ago

@arfon — What if we publish it, wait for the fix, then fix the PDF and update the Crossref deposit? The downside is remembering to do this — I find it ugly to have a published paper with a broken layout.

labarba commented 5 years ago

@wrightaprilm Another option is for you to use the initial only for the second author and also abbreviate the journal title, in the hopes the DOI moves left enough.

Abbreviation from: http://images.webofknowledge.com/images/help/WOS/A_abrvjt.html AMERICAN BIOLOGY TEACHER AM BIOL TEACH

wrightaprilm commented 5 years ago

Let me play with it a bit tomorrow. If I clone Whedon, I can compile within template on my local, correct? That way I can goof around without bothering everyone?

Thanks for all your help - what a weird little hiccup!

labarba commented 5 years ago

Please note this issue I just opened: https://github.com/wrightaprilm/treesiftr/issues/5

labarba commented 5 years ago

@wrightaprilm — You can use the command @whedon generate pdf here, yourself, to see how your changes affect the compiled paper.

wrightaprilm commented 5 years ago

OK, great. I see your issue, and I'm fixing it in a larger 'omnibus' of slightly broken bibtex issues. I have the next 53 minutes earmarked to revise an abstract, but I'll try out a few options for correcting the issue in the morning.

Thanks!

arfon commented 5 years ago

@arfon — What if we publish it, wait for the fix, then fix the PDF and update the Crossref deposit? The downside is remembering to do this — I find it ugly to have a published paper with a broken layout.

Yes, I think we should do this.

wrightaprilm commented 5 years ago

@whedon generate pdf

whedon commented 5 years ago

Attempting PDF compilation. Reticulating splines etc...

whedon commented 5 years ago

:point_right: Check article proof :page_facing_up: :point_left:

wrightaprilm commented 5 years ago

@whedon generate pdf

whedon commented 5 years ago

Attempting PDF compilation. Reticulating splines etc...

whedon commented 5 years ago

:point_right: Check article proof :page_facing_up: :point_left:

wrightaprilm commented 5 years ago

@whedon generate pdf

whedon commented 5 years ago

Attempting PDF compilation. Reticulating splines etc...

whedon commented 5 years ago

:point_right: Check article proof :page_facing_up: :point_left:

wrightaprilm commented 5 years ago

@whedon generate pdf

whedon commented 5 years ago

Attempting PDF compilation. Reticulating splines etc...

whedon commented 5 years ago

:point_right: Check article proof :page_facing_up: :point_left:

wrightaprilm commented 5 years ago

All right, I zapped one of them. There's still a tiny bit of template breaking on the phylogeny.io citation, but I'm happy enough with it. I'd be fine to go ahead, then fix it later.

labarba commented 5 years ago

Feng & Doolittle (1987) has a DOI (not listed): https://doi.org/10.1007/BF02603120 (also, please capitalize the journal name)

Felsenstein (1973) does, too: https://doi.org/10.1093/sysbio/22.3.240

Felsenstein (1978) is https://doi.org/10.2307/2412810

Gower & Ross (1969) is http://doi.org/10.2307/2346439

... please go down the reference list and add any more missing DOIs.

wrightaprilm commented 5 years ago

@whedon generate pdf

whedon commented 5 years ago

Attempting PDF compilation. Reticulating splines etc...

whedon commented 5 years ago

:point_right: Check article proof :page_facing_up: :point_left:

openjournals / jose-reviews