Core Component: Paper Dissection API (v1)

A major release of the DryLab API to deepen the reverse engineering of computational biology papers just rolled out.

Full documentation is available at https://drylab.gitbook.io.

You can now POST a paper (via DOI or PDF), and extract:

• raw methods: /methods/raw

• structured methods: /methods/sections

• raw results: /results/raw

• thematic result blocks: /results/thematic-blocks

• abstracted result modules: /results/thematic-modules

• figure legends: /figure-legends

• supplemental text: /supplement

• mentioned datasets: /datasets

• auto-generate reproducible conda environments from papers: /create-conda-env

the goal is: make code-less, PDF-bound methods programmatically actionable, paragraph by paragraph, module by module.

🔑 Authentication

You can use the API without a key subject to Google Gemini's free tier rate limits.

For real use, just plug in your Google Gemini API key like this with every POST request:

Authorization: Bearer YOUR_API_KEY

takes 2 minutes to set up.

Caveats & what we are working on:

• Primarily tuned for computational biology papers (esp. genomics, transcriptomics).
• Relation extraction accuracy is under active refinement. Send the dev feedback at effie@effie.bio