@_David_Li

BioE PhD Student @Stanford with Hie/Fischbach/Deisseroth labs, previously Scheres group @MRC_LMB via @MarshallScholar, Zhang lab @broadinstitute, @MIT '22

Joined April 2018
Excited to share Minerva, our approach using genome language models for biological discovery! Using Minerva, we find that UG27 reverse transcriptase systems encode variable arrays of diverse ncRNAs with a shared structure, each templating a short DNA hairpin. With @garykbrixi.
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How do lab-in-the-loop ML systems learn most efficiently? How can you pack as much information as possible into an experiment? We explored this in our new preprint “Information-Dense Synthesis for Molecular Discovery” (arxiv.org/abs/2610.08495)
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David Li retweeted
We’re releasing a broad range of new mathematical results produced by an internal frontier model. We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results. github.com/openai/math
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Out now in @CellCellPress: ✨SPARCS✨, a platform for discovering the genes behind complex cellular phenotypes. SPARCS combines Al-powered image analysis with automated laser microdissection to precisely isolate cells from large mutant libraries. Paper and highlights👇(1/9)
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David Li retweeted
Our new paper introduces a scientific theory of atomic features. We mathematically derive testable predictions. Our experiments challenge conventional wisdom. SAEs of different size and training data share many features. Large SAEs recover both parent and child features. 🧵
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The most important briefings of the day. Karl Deisseroth, professor of bioengineering and of psychiatry and behavioral sciences, shares the news of his Nobel Prize with his kids.
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David Li retweeted
Today, our team is sharing a preprint on our new system for generative de-novo enzyme design, AlphaProtein Novo. At @GoogleDeepMind, we have long focused on the building blocks of life (proteins). We developed AlphaFold to predict structure, trained language models to understand function, and built AlphaProteo to design de-novo binders. But proteins play many important roles in nature, such as enzymes that catalyze chemical reactions. Designing entirely new enzymes from scratch to catalyze custom reactions has long been a holy grail for scientists. Our team has shown how AlphaProtein Novo can produce new-to-nature enzymes with state-of-the-art activity on 2 benchmark reactions. We’ve also designed custom enzymes to synthesize the pharmaceutical motif piperidine, and others to degrade the environmental plasticizer toxin DEHP. While there is much more work to do in this direction, we’re excited to have demonstrated the ability to design functional proteins that go beyond what is known in nature. Huge congratulations to @jueseph, @ZvxyWu, Josh Abramson, the @GoogleDeepMind protein design team, and our collaborators in the @francesarnold & Liu Group! 🎉 🔗 Preprints and code: biorxiv.org/content/10.64898… biorxiv.org/content/10.64898… github.com/google-deepmind/a…
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Large archaeal extra-chromosomal elements group into three new families, Klingons, Romulans and Ferengi. These 66-165 kbp circular genomes replicate bidirectionally, unlike linear Borg elements. They encode methylation, glycosylation, protein degradation, TnpB-like enzymes, CRISPR-like arrays, and capsid-like proteins. Klingons and Romulans associate with Methanoperedens, Ferengis with Bathyarchaeaota. The shared gene content of these elements appears to originate from horizontal gene transfer rather than a common origin. doi.org/10.64898/2026.10.02.…
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David Li retweeted
Congratulations to @KarlDeisseroth, Peter Hegemann, and Georg Nagel on the Nobel Prize! I feel very lucky to have learned from all three, from their brilliant science and from their generosity to the scientific community.
To understand how the brain forms memories, feelings and behaviours has long been a dream for researchers. Karl Deisseroth, Peter Hegemann and Georg Nagel have been awarded the 2026 #NobelPrize in Physiology or Medicine for discoveries leading to optogenetics, which makes it possible to switch on, or off, the activity of individual nerve cells in a living brain. This method is now being used in laboratories around the world to reveal the brain’s mysteries.
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BREAKING NEWS The 2026 #NobelPrize in Physiology or Medicine has been awarded to Karl Deisseroth, Peter Hegemann and Georg Nagel “for their discoveries concerning light-gated ion channels and optogenetics.”
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Congratulations to our first #NobelPrize laureate of 2026 🎉 Early this morning Karl Deisseroth found out he was awarded this year's Nobel Prize in Physiology or Medicine. He seems very happy with the news!
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Biosecurity is too important for security theater. In a quick test with Raygun, we found that DeepMind's SynthIDBio watermark signal could be washed out while preserving the predicted structure. We don’t think protein sequence watermarks buy much biosecurity.
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Today, the MitoCarta Tree of Life Consortium (MitoTOL) is releasing high-accuracy mitochondrial proteomes across diverse eukaryotes to empower studies of physiology, evolution, and disease: cell.com/consortium/mitocart… All data can be accessed at: mitocarta.org
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I (fondly) remember as a TA insisting Berkeley undergrads memorize the Krebs cycle and OxPhos ('it's good for your soul,' id say). We'd draw the Krebs cycle as a loop floating free in the mitochondrion, and the respiratory chain as a separate machine in the membrane. In one organism they are bolted together.@VamsiMootha doi.org/10.1016/j.cell.2026.…
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David Li retweeted
1/ Excited to share our new preprint from a joint collaboration between @JswLab + @Bruce_Ksander! Aging is marked by a progressive loss of resilience to stress. Can we systematically search the human ORFome for genes that make vulnerable cells more resilient? Performing such a genome-scale ORF screen led us to NKX2-5—a heart transcription factor we engineered to restore vision, and improve health in aged mice. A breakdown🧵 🔗 doi.org/10.64898/2026.09.29.…
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David Li retweeted
SFT is not dead! 🥳 We found a way to make SFT rival current prevailing posttraining methods, often generalizing better and forgetting less than RL and OPSD. 🤯 Following our prior work on reasoning with sampling, we now introduce sampling to the posttraining stack. 1/n
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David Li retweeted
The devil wears PRADA and now so can cells! Our latest technology-PRADA (Peroxidase Reaction Activated by D-amino Acids) enables in vivo proximity proteomics, transcriptomics, RNA structuromics, and polymer assembly in diverse model organisms. nature.com/articles/s41589-0…
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Our lab's first preprint! The antiphage protein Tiamat is an ATPase and DNase with homologs across the tree of life. What started as undergrad Shirley Yuan's summer project grew into a paper and a collaboration with @jpkbravo's group. Link: biorxiv.org/content/10.64898…
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Out now. A collaboration with Sofia Lövestam, Masato Hasegawa and Sjors Scheres. We report that tau filaments extracted from the brains of individuals with Alzheimer’s disease and corticobasal degeneration breed true in the brains of wild-type mice. nature.com/articles/s41586-0…
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David Li retweeted
Amazing work! NNs learn so many patterns from data, not extraction them for potential discovery always felt like a waste. Also so cool to see the diff heads being predictive of the diff kinds of interactions - very interested to see the representations / motifs that drive these
Excited to share Minerva, our approach using genome language models for biological discovery! Using Minerva, we find that UG27 reverse transcriptase systems encode variable arrays of diverse ncRNAs with a shared structure, each templating a short DNA hairpin. With @garykbrixi.
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