First time at #MLCB! I'll be speaking tomorrow about my development of an ML predictor of domain–peptide interaction affinity to model proteome-scale signaling networks. It'll be livestreamed too.
Thanks Mohammed! I've benefitted immensely from working with creative people like yourself!
Thanks Sam!
Thanks Rocio!
Thanks Trevor!
Thanks Amir!
Congrats to my fellow @jcchildsfund.bsky.social Fellows, @itziknorman.bsky.social and @shiyuxia.bsky.social, and all new awardees!
I am incredibly grateful to so many people for their guidance and support along the way! Especially @moalquraishi.bsky.social who gave a statistical mechanician + molecular biophysicist an opportunity to become a ML’er + system biologist, and encouragement to pursue my own research vision!
I am beyond excited and honored to receive a BWF CASI! This amazing program will support my transition from postdoc to faculty as I continue to develop new modeling frameworks for elucidating and programming cellular behaviors.
AFESM: a metagenomic guide through the protein structure universe! We clustered 821M structures (AFDB&ESMatlas) into 5.12M groups; revealing biome-specific groups, only 1 new fold even after AlphaFold2 re-prediction & many novel domain combos. 🧵
🌐 afesm.foldseek.com
📄 www.biorxiv.org/content/10.1...
Congrats Trevor!!
Small proteins can be more complex than they look!
We know proteins fluctuate between different conformations- but by how much? How does it vary from protein to protein? Can highly stable domains have low stability segments? @ajrferrari.bsky.social experimentally tested >5,000 domains to find out!
Congrats, Dipti!
Structural biology is in an era of dynamics & assemblies but turning raw experimental data into atomic models at scale remains challenging. @minhuanli.bsky.social and I present ROCKET🚀: an AlphaFold augmentation that integrates crystallographic and cryoEM/ET data with room for more! 1/14.
Enjoying #BPS2025! I'll present my development of a ML predictor of domain–peptide binding affinity to understand how affinity is optimized across the proteome for cell signaling. Finish out the meeting by coming to my talk tomorrow (Wed) @ 1pm!
Excited to announce the newest member of the flock - STARLING (conSTruction of intrinsicAlly disoRdered proteins ensembles efficientLy vIa multi-dimeNsional Generative models).
www.biorxiv.org/content/10.1...
Can we learn protein biology from a language model?
In new work led by @liambai.bsky.social and me, we explore how sparse autoencoders can help us understand biology—going from mechanistic interpretability to mechanistic biology.
Super excited to preprint our work on developing a Biomolecular Emulator (BioEmu): Scalable emulation of protein equilibrium ensembles with generative deep learning from @msftresearch.bsky.social ch AI for Science.
www.biorxiv.org/content/10.1...
Could one envision a synthetic receptor technology that is fully programmable, able to detect diverse extracellular antigens – both soluble and cell-attached – and convert that recognition into a wide range of intracellular responses, from gene expression and real-time fluorescence to modulation..
Model Scale vs. Performance curves for ESM C models, with comparisons to ESM2 and other protein LMs. ESMC performs better than existing state of the art for the same model parameter scale.
Introducing ESM Cambrian, a new family of protein language models, focused on creating representations of the underlying biology of proteins.
