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dhimmel avatar dhimmel commented on August 21, 2024 2

@agitter thanks! How about the following citation conventions:

  1. Always use a DOI for the version of record if available. Cite DOIs using [@doi:10.15363/thinklab.4]
  2. If no DOI for the version of record, use a PubMed ID. For example, [@pmid:26158728].
  3. If the article is an arxiv preprint, use [@arxiv:1508.06576].
  4. If the article has none of the above, big problem. File an issue.

You can do multiple citations using: [@doi:10.15363/thinklab.4 @pmid:26158728 @arxiv:1508.06576]

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cgreene avatar cgreene commented on August 21, 2024

Also wanted to tag @YosephBarash and @davek44 who have been active in this area for their thoughts.

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michaelmhoffman avatar michaelmhoffman commented on August 21, 2024

What is the format of the text itself? GitHub markdown?

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michaelmhoffman avatar michaelmhoffman commented on August 21, 2024

Does this need to actually have anything to do with "systems pharmacology"?

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cgreene avatar cgreene commented on August 21, 2024

@michaelmhoffman It should probably roughly touch on topics that could be construed as systems pharmacology. My read is that the precision medicine perspective + deep learning on genomic/transcriptomic/proteomic/etc data gets us close enough.

Format of the text itself will be markdown [eventually I'll convert it to LaTeX and reformat]. I think we will use something like [@doi:doi_link] for citations. @dhimmel has code to automatically pull down doi metadata and covert to bibtex.

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agitter avatar agitter commented on August 21, 2024

Are there any approaches/data types that have taken off in other fields but that are under-utilized here?

Reinforcement learning perhaps? http://karpathy.github.io/2016/05/31/rl/ gives a brief intro. I'm not aware of examples in biology or medicine.

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michaelmhoffman avatar michaelmhoffman commented on August 21, 2024

Reinforcement learning hooked up to some experimental system would be fun.

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dhimmel avatar dhimmel commented on August 21, 2024

@dhimmel has code to automatically pull down doi metadata and covert to bibtex.

@cgreene, the code is here. Let me know when formatting time comes and I can help with the auto-conversion of citations.

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agitter avatar agitter commented on August 21, 2024

@dhimmel that looks great. May want to pair it with Arxiv2bib at formatting time.

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cgreene avatar cgreene commented on August 21, 2024

@dhimmel proposed citation conventions look good to me. Do you want to file a PR to add it to the contribution instructions?

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agitter avatar agitter commented on August 21, 2024

@cgreene there are a lot of Imaging + Bio deep learning papers out there. Should we take a more targeted approach for logging them as issues, such as focusing on those that pertain to human disease and medicine, instead of trying to catalog everything? What might be the main points of this subsection?

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cgreene avatar cgreene commented on August 21, 2024

@agitter : I guess I'd say, if one could make an argument that it's relevant to our current guiding question [which I think still needs a bit of refinement - but probably an increase in specificity, not a decrease] then those are the ones for which we should file an issue.

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cgreene avatar cgreene commented on August 21, 2024

Going to close this now that the discussion has been captured in subsequent issues.

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agitter avatar agitter commented on August 21, 2024

@dhimmel This issue was closed, but I wanted to ask a follow up question now that we're starting to write. The citation conventions above will be great for making the citations machine-readable for automated bibliography construction. Do you have any ideas for how to make them human-readable as well? For example, in latex/bibtex I might use \cite{Zhou2015_deep_sea} so that anyone reviewing my text knows which paper I'm discussing. That will be harder to do when reviewing DOIs and PMIDs.

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dhimmel avatar dhimmel commented on August 21, 2024

Do you have any ideas for how to make them human-readable as well?

DOIs have some semantic meaning (often contain a journal abbreviation). But we could define another category such as [tag:Zhou2015_deep_sea] and then you'd also have to update a mapping file where Zhou2015_deep_sea would point to a valid machine-readable citation. Do you think that is a good solution?

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agitter avatar agitter commented on August 21, 2024

@dhimmel yes, I think that would be the best solution for machine- and human-readable citations. It adds overhead for the authors so we'll have to weigh those tradeoffs.

@cgreene do you have an opinion about creating a citation mapping file?

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cgreene avatar cgreene commented on August 21, 2024

I defer to you and Daniel.

On Thu, Oct 27, 2016, 8:14 AM Anthony Gitter [email protected]
wrote:

@dhimmel https://github.com/dhimmel yes, I think that would be the best
solution for machine- and human-readable citations. It adds overhead for
the authors so we'll have to weigh those tradeoffs.

@cgreene https://github.com/cgreene do you have an opinion about
creating a citation mapping file?


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