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Super cool new paper using AI for structural biology led by Raphael Townshend. This work forms the basis of our new company, atomic.ai, where I'm leading the bioscience team. Can't wait to see how far we can take this!

That was last week. This week: predicting RNA structures with #AI science.sciencemag.org/content/373/65… Raphael Townshend Stanford AI Lab Dror Lab Andrew Watkins Das Lab Ramya Rangan science.sciencemag.org/content/373/65… Science Magazine UNC-Chapel Hill Kevin Weeks explainer

Congrats to Ron Dror, Raphael Townshend, Stephan Eismann, and Masha Karelian at Dror Lab and coauthors at Das Lab for the front page of Science Magazine Geometric deep learning of RNA structure science.sciencemag.org/content/373/65… Perspective science.sciencemag.org/content/373/65… Podcast fcld.ly/n1je7bt

Pleased to announce the speaker lineup for our NeurIPS Conference workshop, ML in Structural Biology, featuring keynotes from John Jumper @DeepMind and Jane Richardson and invited talks by Michael Bronstein, Regina Barzilay, Lucy Colwell Cecilia Clementi, Keating Lab, @Dereklowe

🚨Reminder - submissions for the #MLSB workshop at #NeurIPS2021 are due October 1, Anywhere on Earth (AoE)! Website: mlsb.io Submission: cmt3.research.microsoft.com/MLSB2021

Join us next Monday for an incredible lineup of talks, a panel on the future of ML in structural biology, poster sessions, and virtual happy hour! When: Dec 13, 9am-6pm ET Website: mlsb.io NeurIPS Conference website (needs registration): neurips.cc/virtual/2021/w… 1/🧵

MLSB (Machine Learning in Structural Biology) NeurIPS Conference starting in 30 mins! mlsb.io/#schedule

Starting now!! 🥳 neurips.cc/virtual/2021/w…

The recording of our workshop is now openly available! Fantastic keynotes from John Jumper and Jane Richardson, a panel discussion with our invited speakers, and a fabulous lineup of invited and contributed talks. RT if you want this again next year! mlsb.io

MLSB is back!! Truly an awesome community. Case in point: this was the only virtual event I went to during the pandemic that had a lively happy hour last several hours post close :)

Honored to be nominated to #ForbesUnder30 for my work on #AI and #RNA! Here's to the next 30 years of innovation & discovery! Want to learn more? We are building on this work at Atomic AI (atomic.ai) and are hiring! forbes.com/30-under-30/20…

Great to be returning to MLSB @ NeurIPS at NeurIPS, in-person this time representing Atomic AI! Come by and chat with out team if you are interested in opportunities in ML research in structural biology and RNA! Check out our website atomic.ai to learn more!

It was wonderful to have so many fellow researchers join us for Atomic AI Happy Hour after MLSB @ NeurIPS at last week's NeurIPS Conference. Interested in solving deep technical challenges with ML to cure disease? Come work with us open positions can be found at atomic.ai

What are the functional roles of 3D genome organization? In a new preprint led by Prashant Bhat, we demonstrate a critical role for dynamic 3D organization of genomic DNA around nuclear speckles in controlling the efficiency of mRNA splicing. biorxiv.org/content/10.110…

We’re excited to announce the close of our $35M Series A financing! Atomic AI is fusing artificial intelligence and structural biology to unlock RNA drug discovery, designing RNA-targeted and RNA-based medicines to treat undruggable diseases. businesswire.com/news/home/2023…

It is my pleasure to see Atomic AI's Series A announced today! This is a huge step forward for us as we continue to grow our core AI+structure platform, to help create a new field of RNA drug discovery. Thank you everyone who has been part of the adventure so far! #ml #rna

RNA targeting small molecules This could substantially expand the druggable space, but designing specific & functional binders to RNA is difficult, as we lack quality RNA structures. Atomic AI has built a ML model to predict RNA tertiary structure to guide small molecule design

Exciting work out of the great team at Diffuse Bio on generative protein design, overcoming key limitations in nanobody screening! Nice job Namrata Anand!