Text Content of Website

[sarahjkim]

There are some things I need to complete pages:

1. Phenotype spotlight on Phenotype main page: This is currently "Large floppy ears." Please give me the link for a phenotype that you would like featured as well as a text description for it.
2. Model list on Model main page: There is currently no list of models.
3. Read through Monarch Tour page and let me know if you'd like anything changed.
4. Text in the Release page (and maybe pictures)?

[mellybelly]

The text on the tour page (really the About Monarch page) needs to reference the relationship to NIF. I am taking a pass at that text here, but should be reviewed by @jgrethe, @cmungall and @harryhoch.

Goals Model systems are the cornerstone of biomedical research for understanding of biological processes, testing gene-based disease hypotheses, and developing and testing disease treatments.

There are a wide-variety of model databases that contain unparalleled content about genetics, genomics, anatomy, environmental interactions, and developmental processes. However, clinical and translational researchers face a daunting challenge in using these vast stores of biomedical data to inform their understanding of human disease mechanisms that drives new therapies. This is particularly difficult in the context of rare or undiagnosed diseases, where their data is limited to descriptive phenotypic data and numerous candidate genomic variations.

Currently, tools that exploit similarities between phenotypes, organisms, and human diseases that leverage these rich data are in their infancy or are non-existent. To address this challenge, the Monarch Initiative Discovery System contains a wealth of information about model organisms, in vitro models, genes, pathways, gene expression, protein and genetic interactions, orthology, disease, phenotypes, publications, and authors.

We will provide an ability to navigate multi-scale spatial and temporal phenotypes across in vivo and in vitro model systems in the context of genetic and genomic data, using semantics and statistics. Our system provides basic and clinical science researchers, informaticists, and medical professionals with an integrated interface and set of discovery tools to reveal the genetic basis of disease, facilitate hypothesis generation, and identify novel candidate drug targets. We aim for this system to promote true translational research, in that clinicians can connect with model systems researchers with expertise in related phenotypes, assays, or models.

About the system The Monarch system is built based upon the foundation of the Neuroscience Information Framework (NIF; neuinfo.org). NIF's large scale data ingest system, DISCO, enables the aggregation, provenance, and currency of hundreds of external resources. The Monarch Initiative is performing sophisticated curation and mapping of many of these resources to an integrated suite of ontologies for phenotypes and diseases (https://code.google.com/p/phenotype-ontologies/), genotypes, and anatomy (uberon.org). The ontology services are provided by NIF Ontoquest, and OWLsim enables the comparison of sets of entities across the corpus. Visualization tools to explore this semantic landscape are being developed by the University of Pittsburgh Human computer interactions team. See documentation (add link) for more information.

[harryhoch]

ok, ed On Jan 24, 2014, at 7:46 PM, Melissa Haendel notifications@github.com wrote:

The text on the tour page (really the About Monarch page) needs to reference the relationship to NIF. I am taking a pass at that text here, but should be reviewed by @jgrethe, @cmungall and @harryhoch…

minor edits in the following, including wordsmithing and a bit of extension.

Model systems are the cornerstone of biomedical research for understanding of biological processes, testing gene-based disease hypotheses, and developing and testing disease treatments.

A wide-variety of model databases contain unparalleled content about genetics, genomics, anatomy, environmental interactions, and developmental processes. However, clinical and translational researchers face a daunting challenge in using these vast stores of biomedical data to inform their understanding of human disease mechanisms that drives new therapies. This is particularly difficult in the context of rare or undiagnosed diseases, where data is limited to descriptive phenotypic data and numerous candidate genomic variations.

Currently, tools that exploit similarities between phenotypes, organisms, and human diseases to leverage these rich data are in their infancy or are non-existent. To address this challenge, the Monarch Initiative Discovery System contains a wealth of information about model organisms, in vitro models, genes, pathways, gene expression, protein and genetic interactions, orthology, disease, phenotypes, publications, and authors with semantic similarity calculations that suggest novel relationships based on the information content of data descriptions.

We will provide tools that will use semantics and statistical models to support navigating through multi-scale spatial and temporal phenotypes across in vivo and in vitro model systems in the context of genetic and genomic data. These tools will provide basic and clinical science researchers, informaticists, and medical professionals with an integrated interface and set of discovery tools to reveal the genetic basis of disease, facilitate hypothesis generation, and identify novel candidate drug targets. We aim for this system to promote true translational research, connecting clinicians with model systems researchers who might shed light onrelated phenotypes, assays, or models.

About the system The Monarch system is built based upon the foundation of the Neuroscience Information Framework (NIF; neuinfo.org). NIF's large scale data ingest system, DISCO, enables the aggregation, provenance, and currency of hundreds of external resources. The Monarch Initiative is performing sophisticated curation and mapping of many of these resources to an integrated suite of ontologies for phenotypes and diseases (https://code.google.com/p/phenotype-ontologies/), genotypes, and anatomy (uberon.org). The ontology services are provided by NIF Ontoquest,. The OWLsim algorithmic tools enable the comparison of sets of entities across the corpus. Visualization tools to explore this semantic landscape are being developed by the University of Pittsburgh Human computer interactions team. See documentation (add link) for more information.

[mellybelly]

We need the landing page to have a punchy and short intro.