What if LLMs could “read” & “write” biology? 🤔 Introducing C2S‑Scale—a Yale and Google collab: we scaled LLMs (up to 27B!) to analyze & generate single‑cell data 🧬 ➡️ 📝 🔗 Blog: research.google/blog/teachin... 🔗 Preprint: biorxiv.org/content/10.1...

Teaching machines the language of biology: Scaling large language models for next-generation single-cell analysis

research.google

Excited to share our new preprint: COAST: Intelligent Time-Adaptive Neural Operators! 🌊 We introduce a novel neural operator that learns to dynamically and intelligently adjust time step sizes for modeling dynamical systems from data. 🚀 doi.org/10.48550/arX...

🔥🧠🌌 Now accepted at #ICLR2025 ! How does complexity shape intelligence? 🤔 In our new paper "Intelligence at the Edge of Chaos", we explore the relationship between complex systems and the emergence of intelligence in AI models. Can complexity alone unlock smarter systems? arxiv.org/abs/2410.02536

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.

scGPT-spatial: Continual Pretraining of Single-Cell Foundation Model for Spatial Transcriptomics https://www.biorxiv.org/content/10.1101/2025.02.05.636714v1 🧬🖥️🧪 https://github.com/bowang-lab/scGPT-spatial

1 billion cells feels like a hype number. I’d much rather see a fraction of that with higher quality and much more variation.

10x Genomics@10xgenomics.bsky.social · last yr.

Creating the largest #singlecell dataset ever will take dedication, collaboration & high-performance tools. We’re thrilled the @chanzuckerberg.bsky.social Billion Cells Project will pair GEM-X tech with Ultima Genomics sequencing to achieve this landmark scale. Learn more: bit.ly/4aRaScr

Excited to post my first #skySplain about our recent work published yesterday in Nature Genetics! www.nature.com/articles/s41.... One of the first authors of this study - Annika Vannan – actually wrote this breakdown, but she's not yet over here on bluesky and asked me to post!

Spatial transcriptomics identifies molecular niche dysregulation associated with distal lung remodeling in pulmonary fibrosis - Nature Genetics

Xenium spatial transcriptomic profiling of pulmonary fibrosis characterizes cell composition dynamics and histopathological features associated with the disease.

nature.com

New: The largest medical A.I. randomized controlled trial yet performed, enrolling >100,000 women undergoing mammography screening The use of AI led to 29% higher detection of cancer, no increase of false positives, and reduced workload compared with radiologists w/o AI thelancet.com/journals/lan...

Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, ...

The findings suggest that AI contributes to the early detection of clinically relevant breast cancer and reduces screen-reading workload without increasing false positives.

thelancet.com

Very cool work showing the promise of integrating several sources of data to directly address human health conditions. Synchronized long-read genome, methylome, epigenome and transcriptome profiling resolve a Mendelian condition www.nature.com/articles/s41...

Synchronized long-read genome, methylome, epigenome and transcriptome profiling resolve a Mendelian condition - Nature Genetics

Simultaneous profiling of the genome, methylome, epigenome and transcriptome using single-molecule chromatin fiber sequencing and multiplexed arrays isoform sequencing identifies the genetic and molec...

nature.com

Omega-3 fatty acids had a small protective effect of slowing biological aging (via multiple epigenetic clocks, Figure) nature.com/articles/s43... Exercise and Vit D were also assessed with some additive benefits but not significant on their own

Benchmarking gene embeddings from sequence, expression, network, and text models for functional prediction tasks https://www.biorxiv.org/content/10.1101/2025.01.29.635607v1 🧬🖥️🧪 https://github.com/ylaboratory/gene-embedding-benchmarks

Fruitful collaboration between our team & Sven Jager/Ziv Bar Joseph's team @Sanofi published today @narjournal.bsky.social: a language model that learns the grammar of all regions of an mRNA from head to tail!! Can be fine-tuned on all of your favorite mRNA-related tasks -- a successor of CodonBERT.

mRNA-LM: full-length integrated SLM for mRNA analysis

Abstract. The success of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) messenger RNA (mRNA) vaccine has led to increased interest in the des

academic.oup.com

Our op-ed @nytopinion.nytimes.com today addresses the surprising results of recent medical studies that showed A.I. alone outperformed physicians using A.I. W/@rajpurkar.bsky.social Here is a summary Table, an overview, and a gift link to the op-ed erictopol.substack.com/p/when-docto...

When Doctors With A.I. Are Outperformed by A.I. Alone

Interpreting Some Surprising Results

erictopol.substack.com

We do see strong scaling laws in single cell foundation models

Jacob Schreiber@jmschreiber91.bsky.social · 2y ago

Genomic Foundationless Models: Pretraining Does Not Promise Performance I've long believed genomic foundation models are not as useful as claimed. In my mind, there isn't enough training data to justify their size. Interesting to see more work in this direction. www.biorxiv.org/content/10.1...

A month ago we @vevotherapeutics.bsky.social announced that we have generated the largest single-cell perturbation atlas in history, Tahoe-100M. Today, we announce that we will fully open-source Tahoe-100M in Feb, as part of a collaboration with NVidia health to train cell state models.

Excited to share our new study of #genomics🧬, #EHR📈 + treatment outcomes of 78K patients across 20 #cancers! We identified >700 mutations predicting which drugs💊 are effective for individual patients. Our #ML model predicts who responds well to immunotherapies. #precisioncancer

Our ChromBPNet preprint out! www.biorxiv.org/content/10.1... Huge congrats to Anusri! This was quite a slog (for both of us) but we r very proud of this one! It is a long read but worth it IMHO. Methods r in the supp. materials. Bluetorial coming soon below 1/

ChromBPNet: bias factorized, base-resolution deep learning models of chromatin accessibility reveal cis-regulatory sequence syntax, transcription factor footprints and regulatory variants

Despite extensive mapping of cis-regulatory elements (cREs) across cellular contexts with chromatin accessibility assays, the sequence syntax and genetic variants that regulate transcription factor (T...

biorxiv.org

Anshul Kundaje@anshulkundaje.bsky.social · 2y ago

Aiming to release our long awaited ChromBPNet preprint by early next week as well. I'm recovering from back to back infections for the past 6 weeks. But we're almost there. We have some solid variant prediction benchmarks in there against large supervised models and lots more. Stay tuned.

First 🦋 post! Very excited to share our lab's latest work exploring the shared and divergent aspects of human astrocyte development and glioblastoma. This effort spans many fields from developmental #glial biology to #stem cells and #tumor biology. rdcu.be/d5ADz A 🧵

Mapping the developmental trajectory of human astrocytes reveals divergence in glioblastoma

Nature Cell Biology - Sojka et al. analyse the transcriptomic and epigenomic landscape of human astrocyte maturation and identify an epigenetically regulated intermediate state associated with...

rdcu.be

Out today in @naturegenet.bsky.social -- PERFF-seq! With @tsionabay.bsky.social , @ronanchaligne.bsky.social, Bob Stickels, Meril Takizawa, + Ansu Satpathy, we describe this new assay to study rare populations with programmable nucleic acid cytometry. 1/n www.nature.com/articles/s41...

Transcript-specific enrichment enables profiling of rare cell states via single-cell RNA sequencing - Nature Genetics

Programmable Enrichment via RNA FlowFISH by sequencing (PERFF-seq) isolates rare cells based on RNA marker transcripts for single-cell RNA sequencing profiling of complex tissues, with applicability t...

nature.com

Seeking pioneering scientists in immunology, neuroscience, and machine learning! Join Arc Institute as a Core Investigator + Stanford Bioengineering as Associate/Full Professor. Full lab funding and cutting-edge facilities in Palo Alto. Apply by Jan 15 for full consideration: shorturl.at/CuH1K

Associate or Full Professor Rank Search to join the Arc Institute as a Core Investigator and the Stanford Department of Bioengineering | Arc Institute

Arc Institute is a independent nonprofit research organization headquartered in Palo Alto, California.

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