Biology needs to move faster. Generative AI can transform how bioinformaticians work. 🚀 Launching Nucleus, an open-source project to help bio pros transform, visualize & analyze multi-omics files—right from the terminal. #Bioinformatics #OpenSource #AI

I just read an incredible paper. These authors went and used sequencing data from the U.K. Biobank and found that a sizable number of people were likely misdiagnosed with a common disease when they really have a rare one. The next part was amazing: They looked at sequencing

Ask not why would you work in biology, but rather: why wouldn't you? https://t.co/7zkdjniFQ9 openai/gemini gave this essay an A- for evocative imagery. claude gave it a C- for being emotionally manipulative. both are probably right. i feel a little sick re-reading it

TIL the coffee maker at Lalbagh MTR has been at it since 1977. Talk about being locked in. ☕️🔥

Applications are now open for the Thrive Capital Fellowship next summer; it’s for college students, full-time, and a paid 10 week internship - come join @ThriveCapital to invent and learn with our team 👇

Blr is the only serious indian city where ideas are a first class citizens, how u dress or look hardly influences partnerships, raising the ceiling is more important than raising the floor and the action anxiety is normal

(New thesis) AI-ification of R&D proteins There’s been an emergence of new papers on computational antibody, peptide, nanobody, and and enzyme design. While these are all relevant for new therapeutics, there’s massive market opportunity in R&D reagents. (This thesis was started

ProteinDJ: a high-performance and modular protein design pipeline | bioRxiv https://t.co/luzgb9U8dP

Can machine learning design functional antibodies without specialized training, and at what success rates?@ManifoldBio @biorxivpreprint "mBER: Controllable de novo antibody design with million-scale experimental screening" • Antibody therapeutics dominate protein drug

Another promising VHH model just dropped today from @ManifoldBio. This one builds on BindCraft and ColabDesign. MIT license! https://t.co/zMvYRY4uEI The success rates appear to be lower than other tools, but this is highly target-dependent.

New in-depth blog post time: "Inside NVIDIA GPUs: Anatomy of high performance matmul kernels". If you want to deeply understand how one writes state of the art matmul kernels in CUDA read along. (Remember matmul is the single most important operation that transformers execute

New blogpost on the latest in AI antibody design. Including some code to easily run Germinal and IgGM on modal! https://t.co/G2ZC6fzUxq

On Arattai, we have initiated discussions with Sharad Sharma of iSpirt, the group that did the technical work to make UPI happen, to standardize and publish the messaging protocols. I am a huge fan of UPI and hugely respect the work the team did. Sharad is a good friend and he

We have faced a 100x increase in Arattai traffic in 3 days (new sign-ups went vertical from 3K/day to 350K/day). We are adding infrastructure on an emergency basis for another potential 100x peak surge. That is how exponentials work. As we add a lot more infrastructure, we are

Building on more remarkable work by @arcinstitute to markedly expand the capabilities for human genome editing ("CRISPR 3.0"). Watch our conversation just after their discovery of Bridge RNAs https://t.co/EW9xFCO4O7

Paving the way for unlimited context windows. Introducing @zml_ai /attnd: sparse logarithmic attention, on CPU, over UDP, faster than GPU.

She’ll never post this — too humble. But for the 2nd year running, my wife has been recognized among the "Top 2% scientists in the world" by @Stanford for her pioneering work in autonomous vehicle security. Born in a small town in Haryana, working today as a faculty at NIT in

(1/6) triton kernels are a great way to understand ML models. but tutorials are scattered the learning method for me was jst to read real, high performance code so i wrote a blog which walkthroughs the design and intuitions behind FLA's softmax attention kernel 🧵also a thread

Excited to share that my PhD thesis work is out in @ScienceMagazine today. We demonstrate robust rearrangement of the human genome using bridge recombinases, performing programmable insertions, excisions, and inversions at megabase-scale.

For decades, human genome editing has been limited to small, localized modifications. Today, in a new paper published in @ScienceMagazine, researchers from the @pdhsu lab show that bridge recombinase technology is capable of large-scale genomic rearrangements in human cells.

In another preprint from the @brianhie Lab and @SynBioGaoLab, they introduce Germinal, a generative AI system for de novo antibody design. Germinal produces functional nanobodies in just dozens of tests, making custom antibody design more accessible than ever before.