Debora Marks

Hey / let’s stop with the AI meme and talk about computational learning. Depoliticize it.

1/ For over a decade, my lab and others have shown you can predict 3D structure of proteins, it’s interactions, which mutations may cause disease and even how a virus evolves - all from evolutionary sequence data

2/ Whilst powerful - our approaches are still missing what we really need: how natural variation or design ripples through transcription, translation, complex assembly, and the behavior of the cell/tissue organism it's sitting in. Call that mechanism, etiology, pathophysiology, but it’s where we need new models.

3/ GenBio AI (where I am an advisor) is previewing AIDO Cell today: genbio.ai/aido-cell-simu… one model spanning DNA, RNA, protein, and whole-cell behavior, so a variant's consequences can be traced forward instead of just scored. The technical report here nice is a way to release the progress.

#AI for #proteindesign is a done deal so is it time to

Meet evedesign: a new open-source ML framework that makes protein design accessible and interoperable.

📢 See our post: deboramarkslab.substack.com/p/evedesign-bi…

Protein design models are powerful, but combining them shouldn’t require custom glue code.

✅Combine models for multi-objective optimization
✅Integrate lab-in-the-loop experimental of data
✅100% secure: run on your own infra, no data sharing

Get started building therapeutics & industrial enzymes today 👇
📄Paper: biorxiv.org/content/10.648…
💻Code: github.com/evedesignbio
🌐Webserver: evedesign.bio

Reach out to collaborate: hello@evedesign.bio

Such a relief to see work like this .. now we can get on with the real challenges! Thx @CarldeBoerPhD and team - missed this when you first posted

biorxiv.org/content/10.110…