xarray-contrib / xarray-contrib/xarray.dev

[User story proposal] Describe Xarray for protein ML/AI work

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user-story
Dominant language
JavaScript
Stars
14
Forks
30
Avg merge
6h 47m
Merged PRs (30d)
1

Description

This is a proposal for a sequencing/protein engineering use case story for Xarray. The story will be published on Xarray's blog (https://xarray.dev/blog).

Why?

@asford and colleagues are quite excited about using Xarray +torch for generative ML models and "protein engineering". It'd be nice to broadcast this out.

It's also interesting that they find coordinate variables quite useful and so DataArray is the right structure rather than Variable/NamedArray/pytorch.NamedTensor

What?

We are targeting a short and non-technical post that illustrates how Xarray is (or could be) used in your genomics context. Below is a template outline that you should feel free to modify:

  1. Who am I?
  2. What problem am I trying to solve?
  3. How does Xarray help?
  4. Why did I choose Xarray?
  5. Current pain points (or ways that Xarray could better serve your use case)
  6. Technology I use around Xarray
  7. Anything else to know?
  8. Links and references

Feel free to insert images or short code blocks if they help you tell your story.

How?

Xarray's blog using Markdown with some front-matter. You can copy one of the existing posts to get started or you can write in a google-doc-like-thing and ask us to do the markdown formatting. If you copy a previous post, use a name like user-story-genomics or whatever makes sense for your application.

xref: https://github.com/xarray-contrib/xarray.dev/issues/272

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Review the existing Markdown posts in xarray.dev's src/posts and their front matter, then use the proposed outline to gather or draft a short protein-engineering user story. Done means the story is ready for publication on the Xarray blog, with any useful images, code blocks, links, and references included.

Written by the indexing model from the issue text.

Assessment

Tech stack
markdown, pytorch
Domain
content, documentation, machine-learning
Issue type
Documentation
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Clearly specified
Newbie friendliness
35/100

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