Agents for comp bio are advancing rapidly, but evals are lagging. Current benchmarks can be overly prescriptive. Full analysis vignettes are hard to verify. We introduce CompBioBench: 100 diverse, challenging, verifiable tasks. We benchmark Codex and Claude Code. biorxiv.org/content/10.6... 1/9

New preprint! Our workflow for processing single cell and nuclei data, called 🎉 scprocess 🎉 We have been working on it for ~18 months now, over which time we have processed at least 2k samples with it, so it has had a decent amount of testing.

#SingleCell preprints@prepub-singlecell.bsky.social · 5mo ago

scprocess: a pipeline for processing, integrating and visualising atlas-scale single cell data #SingleCell 🧪🧬🖥️ https://www.biorxiv.org/content/10.64898/2026.03.09.710141v1

Together with Ehsan Hajiramezanali, we are looking for PhD students for a Summer 2026 research internship at the intersection of LLMs, agentic AI, active learning, and biological sequence design. Applications now open, two weeks to apply: roche.wd3.myworkdayjobs.com/ROG-A2O-GENE...

We are hiring a PhD intern for Summer 2026 in ML for regulatory genomics at ReLU/BRAID/Genentech! Work on DNA sequence models for the noncoding genome (e.g. DNA design, models of MPRA and genetic variants)! 🥳

2026 Summer Intern - Biology Research | AI Development in South San Francisco, California, United States of America | Students & Graduates at Genentech

Apply for 2026 Summer Intern - Biology Research | AI Development job with Genentech in South San Francisco, California, United States of America. Students & Graduates at Genentech

lnkd.in

Introducing Nona! 🧬 @suragnair.bsky.social 's brilliant idea to unify siloed genomic AI. Nona learns jointly from DNA seq + functional data, enabling new ways of modeling genomic data!

Surag Nair@suragnair.bsky.social · 9mo ago

Excited to share Nona: a unifying multimodal masking framework for functional genomics. Models for DNA have evolved along separate paths: sequence-to-function (AlphaGenome), language models (Evo2), and generative models (DDSM). Can these be unified under a single paradigm? 1/15

Nature research paper: Specificity, length and luck drive gene rankings in association studies go.nature.com/47Fsqax

Specificity, length and luck drive gene rankings in association studies - Nature

Genetic association tests prioritize candidate genes based on different criteria.

go.nature.com

We have a postdoc position in my team. Join us if you are passionate about genomics, human genetics, synthetic biology and agentic AI! careers.gene.com/us/en/job/20...

gReLU advances deep learning based modeling and analysis of DNA sequences with comprehensive toolsets and versatile applications. @avantikalal.bsky.social @gokcen.bsky.social www.nature.com/articles/s41...

gReLU: a comprehensive framework for DNA sequence modeling and design - Nature Methods

gReLU advances deep-learning-based modeling and analysis of DNA sequences with comprehensive toolsets and versatile applications.

nature.com

I'm happy to share that our gReLU package is now published in Nature Methods! www.nature.com/articles/s41...

gReLU: a comprehensive framework for DNA sequence modeling and design - Nature Methods

gReLU advances deep-learning-based modeling and analysis of DNA sequences with comprehensive toolsets and versatile applications.

nature.com

We have a postdoc position in my team. Join us if you are passionate about genomics, human genetics, synthetic biology and agentic AI! careers.gene.com/us/en/job/20...

My team has a postdoc position available now, join us! careers.gene.com/us/en/job/20...

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 🧵👇

bioRxiv Genetics@biorxiv-genetic.bsky.social · last yr.

Benchmarking DNA Sequence Models for Causal Regulatory Variant Prediction in Human Genetics https://www.biorxiv.org/content/10.1101/2025.02.11.637758v1