Can we simulate realistic evolutionary trajectories and “replay the tape of life”? In this work, we propose a flexible, generalizable deep learning framework for modeling how the entire protein sequence evolves over time while capturing complex interactions across sites. 1/n doi.org/10.64898/202...

Published online on Jan 2, 2025 and just appeared in the December 2025 issue!

The registration deadline is fast approaching for probgen 2026! Abstracts due by January 15, registration by January 31 probgen2026.github.io

Over the past 5+ years I've had the honor of working with @wsdewitt.github.io @victora.bsky.social and many others on a project to "replay" affinity maturation evolution from a fixed starting point. matsen.group/general/2025...

Organisers - Shu Zhang | @gladstoneinst.bsky.social Invited Speaker - @yun-s-song.bsky.social | @ucberkeleyofficial.bsky.social

How to keep in step when your (protein) partner speeds up… Here we investigated the adaptive remodeling of a protein-protein interaction surface essential for telomere protection. Congrats to whole team! www.science.org/doi/10.1126/...

The last work of my PhD is finally out: www.pnas.org/doi/10.1073/...! This work is about accurately estimating branch length in the Ancestral Recombination Graph (ARG), which is achieved by a really simple framework with minimal assumptions. (1/n)

An open-rank faculty search in AI + Engineering (Bioengineering included) at UC Berkeley. Due date: Monday, Nov 3, 2025 at 11:59pm (PT) Please help spread the news. aprecruit.berkeley.edu/JPF05144

This is truly an incredible breakthrough IMO. Really exemplifies what you get when deep domain expertise (popgen/evolution/disease genetics in this case) fuses with cleverly crafted ML. What u get r sleek, well thought out architectures that absolutely destroy the behemoths. Wow!! 1/

We are excited to share GPN-Star, a cost-effective, biologically grounded genomic language modeling framework that achieves state-of-the-art performance across a wide range of variant effect prediction tasks relevant to human genetics. www.biorxiv.org/content/10.1... (1/n)

SINGER, our ARG inference method, is finally published and freely available online: doi.org/10.1038/s415... It was a long journey – 16 months from initial submission to acceptance. Is it just me, or has peer review gotten more arduous lately? 4+ rounds of review isn't so unusual these days...

Hi Bluesky — Dedicating my first post to this work and software, led by the incredibly meticulous and capable @fandingzhou.bsky.social! An earlier version of this was shared at the 2022 Bioconductor Conference (bioc2022.bioconductor.org/schedule/).

Gene expression changes aren’t just about mean shifts — variability shifts matter too, especially for aging. We're thrilled to introduce QRscore, a flexible non-parametric framework for detecting shifts in mean and variance across conditions. doi.org/10.1016/j.cr...

In a new preprint we use deep learning on lineage trees to infer the functional form of the relationship between affinity and fitness that controls antibody evolution in germinal centers: arxiv.org/abs/2508.09871 🧵

Antibodies are highly diverse, but most possible sequences are unstable or polyreactive. In this work, just published in Cell Syst., we propose a new source of data for modeling constraints from these properties. Our models show clear improvements in predicting Ab dysfunction. (1/n) t.co/qCZERPUMPF

(1/4) 🧬 Why Sequence the Genomes of Earth’s Biodiversity? The Earth BioGenome Project 🌍 is a global network of initiatives working together to create a complete genome library for all Eukaryotic life—from mushrooms 🍄 to mammals 🐘. #biodiversity #genomes #sequence #earthbiogenome #education #stem

Germinal center clonal diversity trees as a musical score, a great image to start @victora.bsky.social's CCII seminar, "Replaying germinal center evolution on a quantified affinity landscape" #GerminalCenter #Immunology www.ccii.med.kyoto-u.ac.jp/en/event/the...

In vivo mapping of mutagenesis sensitivity of human enhancers www.nature.com/articles/s41...

The 2026 Probabilistic Modeling in Genomics (ProbGen) meeting will be held at UC Berkeley, March 25-28, 2026. We have an amazing list of keynote speakers and session chairs: probgen2026.github.io Please help spread the news.

Wanted to highlight our latest preprint--a huge effort by multiple people and labs, but led primarily by @wsdewitt.github.io, Tatsuya Araki, and Ashni Vora, in a very close wet-dry collaboration with @matsen.bsky.social’s lab at the Hutch www.biorxiv.org/content/10.1...

Check out CRISPRpedia, our resource on all things #CRISPR! The latest chapter is on CRISPR & ethics: innovativegenomics.org/crisprpedia/... CRISPRpedia features 85+ original illustrations that are free to download & use for non-commercial purposes! #STEMeducation #STEMed #bioethics #SciArt

How well can deep learning models predict the effect of modifying chromatin on gene expression??? Our work -- led by Sanjit Batra and Alan Cabrera when they were in @yun-s-song.bsky.social ’s and Isaac Hilton’s labs -- tries to answer this. 🧵🧬🧪 elifesciences.org/reviewed-pre...

New preprint in collaboration with @paulinanunezv.bsky.social supervised by @jonnyfrazer.bsky.social and Mafalda Dias – we propose a simple approach to improving zero-shot variant effect prediction in pre-existing protein and genome language models: 🧶 1/n www.biorxiv.org/content/10.1...

How can one efficiently simulate phylodynamics for populations with billions of individuals, as is typical in many applications, e.g., viral evolution and cancer genomics? In this work with M. Celentano, @wsdewitt.github.io , & S. Prillo, we provide a solution. doi.org/10.1073/pnas... 1/n

In a medical breakthrough, a team including IGI’s @urnov.bsky.social & @giannikopoulosp.bsky.social created an on-demand #CRISPR therapy for an infant with a deadly gene mutation — developed, approved, and delivered to the patient in just 6 months. Read more: ow.ly/G0Bg50VTonC #RareDisease 🧬

Jennifer Doudna @jenniferdoudna.bsky.social @doudna-lab.bsky.social speaks with Cleo Abrams on the history and future of #CRISPR 🧬. Watch here: youtu.be/0OXaanDHENI?...

Overfitting is among the conceptually most interesting problems in machine learning. I am happy of several new phenomena we began to understand with Pierfrancesco Urbani. Alert: mostly non-rigorous! (Celebrating Jorge Kurchan) web.stanford.edu/~montanar/OT...

If you want to check if a human gene has copy-number changes or lands in a complex region, try pangene.bioinweb.org. Recently updated with more and better assemblies.

Thrilled to see my digital art on the cover of Trends Genet. The two binary strings represent reverse-complementary DNA sequences (00=A, 01=C, 10=G, 11=T) and the connecting rectangles represent “embeddings” learned by DNA language models. Pls check out our article as well: doi.org/10.1016/j.ti...

In our updated TraitGym preprint (w/ @gonzalobenegas.bsky.social & Gökcen Eraslan), we evaluate Evo 2 on regulatory variants associated with human traits. We see marked performance gains with scale on Mendelian traits, although still a bit behind alignment-based methods. doi.org/10.1101/2025... 1/n

Can DNA sequence models predict mutations affecting human traits? We introduce TraitGym, a curated benchmark of causal regulatory variants for 113 Mendelian & 83 complex traits, and evaluate functional genomics and DNA language models. Joint work w/ Gökcen Eraslan and @yun-s-song.bsky.social 🧵👇

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.

Our work, which shows statistical issues with the previous claim of a severe ancient bottleneck in the ancestry of African populations, has been selected as a Featured article in Genetics. doi.org/10.1093/gene...

Coincidentally, another article from my lab on DNA language models got published on the same day as GPN-MSA. It's freely available for 50 days from this link: authors.elsevier.com/a/1kNCscQbJB... Genomic language models: opportunities and challenges Please share with your colleagues.

Happy New Year! Our GPN-MSA paper is finally published, under a slightly different title from the preprint. Please check it out and share it with your colleagues: doi.org/10.1038/s415... 1/4

What do GWAS and rare variant burden tests discover, and why? Do these studies find the most IMPORTANT genes? If not, how DO they rank genes? Here we present a surprising result: these studies actually test for SPECIFICITY! A 🧵on what this means... (🧪🧬) www.biorxiv.org/content/10.1...

Thrilled to share our approach for language model-guided discovery of unknown mammalian metabolites: DeepMet. We’ve now used this approach to discover ~50 new human and mouse metabolites! www.biorxiv.org/content/10.1...

Large protein language models can learn complex epistatic interactions, but how much does that help with predicting variant effects? In this NeurIPS article, we show that classical independent-sites phylogenetic models can outperform pLMs on this task. 1/7 openreview.net/forum?id=H7m...