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David van Dijk

@vandijklab.bsky.social
115 followers 46 following 51 posts

Learning the rules of life. Assistant Professor of Medicine and Computer Science @ Yale

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David van Dijk @vandijklab.bsky.social · 18/04/2025
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...
research.google
Teaching machines the language of biology: Scaling large language models for next-generation single-cell analysis
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David van Dijk @vandijklab.bsky.social · 13/02/2025
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...
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David van Dijk @vandijklab.bsky.social · 12/02/2025
🔥🧠🌌 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
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Etowah Adams @etowah0.bsky.social · 10/02/2025
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.
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Stephen Turner @stephenturner.us · 10/02/2025
scGPT-spatial: Continual Pretraining of Single-Cell Foundation Model for Spatial Transcriptomics www.biorxiv.org/content/10.1101/202… 🧬🖥️🧪 github.com/bowang-lab/scGPT-spatial
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Kendall Reid @kendallreid.bsky.social · 06/02/2025
1 billion cells feels like a hype number. I’d much rather see a fraction of that with higher quality and much more variation.
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Nick Banovich @nebanovich.bsky.social · 04/02/2025
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!
nature.com
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.
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Eric Topol @erictopol.bsky.social · 04/02/2025
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...
thelancet.com
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.
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Jacob Schreiber @jmschreiber91.bsky.social · 03/02/2025
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...
nature.com
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...
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Eric Topol @erictopol.bsky.social · 03/02/2025
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
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Stephen Turner @stephenturner.us · 03/02/2025
Benchmarking gene embeddings from sequence, expression, network, and text models for functional prediction tasks www.biorxiv.org/content/10.1101/202… 🧬🖥️🧪 github.com/ylaboratory/gene-embeddi…
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Vikram Agarwal @vagar.bsky.social · 03/02/2025
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.
academic.oup.com
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
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Eric Topol @erictopol.bsky.social · 02/02/2025
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...
erictopol.substack.com
When Doctors With A.I. Are Outperformed by A.I. Alone
Interpreting Some Surprising Results
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David van Dijk @vandijklab.bsky.social · 03/02/2025
We do see strong scaling laws in single cell foundation models
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Hani Goodarzi @genophoria.bsky.social · 13/01/2025
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.
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James Zou @jameszou.bsky.social · 08/01/2025
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
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Anshul Kundaje @anshulkundaje.bsky.social · 25/12/2024
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/
biorxiv.org
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...
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Steven Sloan @sloanlab.bsky.social · 08/01/2025
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 🧵
rdcu.be
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...
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Caleb Lareau @caleblareau.bsky.social · 08/01/2025
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...
nature.com
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...
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Arc Institute @arcinstitute.org · 08/01/2025
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
arcinstitute.org
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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