greenelab / deep-review

A collaboratively written review paper on deep learning, genomics, and precision medicine
https://greenelab.github.io/deep-review/
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Potential Reorganization #1005

Open manolik opened 4 years ago

manolik commented 4 years ago

Hi all, This is such an awesome review, and i'd love to use it as a basis for teaching, but i've had to jump back-and-forth through sections, as the current structure doesn't flow as naturally for a class. I had some thoughts about potentially restructuring and wanted to get folks' feedback on this. What do you think? https://www.dropbox.com/s/guv6eovze8e1s6g/Deep%20Learning%20Review%20Reorganization.xlsx?dl=0 Thanks! Manolis image

agitter commented 4 years ago

@manolik this is great, thanks for the suggestions. I see many benefits to a major reorganization:

The only real downside is that it will take more effort to write and especially to edit. I'm okay with that. If we put out a call for help with specific pieces, we can attract domain experts to contribute.

If others generally think this is a good idea, we can create add a new outline to the repository starting from the spreadsheet above.

akundaje commented 4 years ago

I support the idea of a re-org as well

cgreene commented 4 years ago

I also strongly support the idea of reorganization. I wonder if it would make sense to have a Imaging, Text, and EHR (perhaps in that order?) in a module. EHRs are hot as an area, but it might help to lead off with how folks are handling many of the components of them before jumping into them.

I made @manolik's into a markdown version of the table.

Introduction -1 DL's role outside of biology
How this document was composed (online, open, living) & context for those who read prior version
Module0 0 Foundations ML and Deep Learning
CNNs, RNNs, Model Architectures
Training, Regularization
Dimensionality reduction
Autoencoders, Generative Models, GANs
Module1 1 Pre-Tx DNA accessibility
Promoters and enhancers
Transcription factors
DNA methylation
2 Expression Gene expression
Single-cell data
3 Post-Tx Splicing
Micro-RNA binding
Module2 4 Variation Sequencing and variant calling
Comparative genomics
Alignment, Evolution
5 Genetics Population genetics, phasing
eQTLs
Genetics, GWAS, Rare variants
6 EHRs Patient categorization
Electronic health records
7 Specialized Neuroscience
Metagenomics
Cancer
Module3 8 PPIs Protein-protein interactions
PPI networks and graph analysis
9 Protein Structure Protein secondary and tertiary structure
Structure determination and cryoEM
10 3D structure MHC-peptide binding
11 Therapeutics Drug development
Drug repositioning
Module4 12 Imaging Morphological phenotypes
Imaging applications in healthcare
Video processing and analysis
13 Text Text applications in healthcare
Clinical decision making
Interactive question/answer systems
Module5 14 Models Customizing: bias-vs-variance
Uncertainty quantification
Multimodal, multi-task, and transfer learning
Interpretation
15 Practical issues Optimization
Data limitations
Hardware limitations and scaling
Data, code, and model sharing
Module6 16 Conclusions Summarize how field has changed since prior review (mid 2017)
17 Methods Summarize number of contributors, number of commits, use of manubot, etc. Primarily for others undertaking similar efforts.

I added a brief intro / conclusions section. While I could see the adjustments I proposed, I think they are small when compared to the scale of the reorganization. I like where this is going and strongly support this concept! 👏

manolik commented 4 years ago

Yes, greatly agree.

  1. about intro on "DL beyond bio". To avoid distracting from the main message, I would perhaps put this as a section at the end of the "Module0.Foundations" module, after introducing the core methods, which i think are more relevant.

  2. About how the article was written, i would add that to the beginning of Module6-section 17, as folks reading this article/book will care more about the content than the (very awesomely cool) way it was written

evancofer commented 4 years ago

I agree. Reorganizing things in this manner looks like a good idea.

SystemsResearch commented 4 years ago

This structure looks good. I am just wondering if sections 6 and 7 would be fit better later on. The progression could be:

cgreene commented 4 years ago

I do think imaging, text, and EHRs make a lot of sense together. Perhaps what's currently "specialized" could have it's own module just before Module 5. These sections would likely be shorter, but that's ok. Sleep, if I understand correctly, might go into neuroscience there for instance.