No More GIL! the Python team has officially accepted the proposal. Congrats Sam Gross on his multi-year brilliant effort to remove the GIL, and a heartfelt thanks to the Python Steering Council and Core team for a thoughtful plan to make this a reality. discuss.python.org/t/a-steering-c…

Check out our latest paper describing a novel 'RNA array design strategy' for creating tunable RNA circuits that function across different microbes! A big congrats to Baiyang Liu who led the work and our collaborators @FrancoLabUCLA Matthew Bennett nature.com/articles/s4146…

This. Starting with C only makes you a strong programmer overall.

Today we announced FDA clearance of our IND application for SENTI-202, a potential first-in-class, logic-gated treatment for acute myeloid leukemia. Learn more: bit.ly/3v4IMJY $SNTI #AML #CARNK

Do you need a billion parameters and millions of sequences for #proteindesign? Maybe not! See our paper: shorturl.at/novMO We show that interpretable, non-autoregressive structure-based protein design can work! Original thread: shorturl.at/cdgCP

If you are using Language Models to predict gene expression, you better compare with latest state-of-the-art biophysical or ML models

Please RT: If there's an old unmaintained software that is prohibitively slow and is only one of its kind do you not benchmark your new tool against it? How to properly address reviewers and frame this issue in paper?

In our newest preprint, • we explore the effects of synonymous genome recoding, and • construct & troubleshoot a synthetic 57-codon E. coli genome using multi-omics, editing, and laboratory evolution. 1/n

After almost two years of optimization, SynOMICS's plasmid system is a fusion of David Bikard @MarraffiniLab's Cas9 & the pORTMAGE plasmids & ELSA/nonrepetitive parts by Howard Salis Ayaan Hossain Alex Reis & co I highly recommend using multiplexed sgRNAs from nature.com/articles/s4158…

Supremely entertaining paper, "ChatGPT is bullshit": link.springer.com/article/10.100…

Thanks for the highlight DOE Office of Science! Read more about our research: nature.com/articles/s4158… biorxiv.org/content/10.110…

I am pleased to announce our latest publication ‘Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning’ in Nature Communications

This is a great paper from the Howard Salis lab. - Measure the decay rates of 50,000 mRNAs in bacteria. - Use biophysical models + ML to build models of mRNA stability. - Profit. And a good reminder of what's possible when one turns a biological problem into a sequencing problem!

If you have a solid strategy and a small amount of compute, you can go pretty far. If you have huge clusters of GPUs and no strategy, your only achievement will be burning capital.

🚨 New preprint 🚨 We introduce Generative Distribution Embeddings (GDEs) — a framework for learning representations of distributions, not just datapoints. GDEs enable multiscale modeling and come with elegant statistical theory and some miraculous geometric results! 🧵

New lab preprint! 🚀 Modeling complex data distributions is tough. We designed GDEs, a new framework that tackles this head-on! GDEs generalize across text, images & MANY bio apps (think virtual cells, spatial bio, viral genome tracking). Thread 👇

🧠 Why do smart scientists feel stupid when reading papers? Because nobody teaches you HOW to read them efficiently. This 3-pass system will change how you approach every paper: 🧵