Why bioRxiv
Posts by Arjun Raj
Thank you. My colleagues and I are pleased that we developed a system that works and that 11 years and over 100 papers #gastruloid papers later, what we felt in the final paragraph of the paper is coming along. There is now a community improving and learning from the system.
Grateful to have worked with such an incredible team on this project. Excited to finally share this story about Top2 evolution and hybrid incompatibility in Drosophila. More to come!
Hope you like it! It’s one of my very favorite papers from the lab ever.
I had two undergrads in my office today working on a computational project. My normal advice in research is to use tools to their fullest to get to the cutting edge. For the first time, I was reluctant. I worry that using coding agents would rob them of something. And I’m fully AI-pilled.
🧮 Check things that should add up
⚠️ Never ignore code warnings
📊 Track datapoints like the number of rows
🔍 Investigate outliers
🧠 If something doesn’t make sense, keep digging
arjunrajlab.substack.com/p/transition...
AI is pushing computational biology into analytic abundance.
The bottleneck is no longer generating results: It’s deciding whether to trust them. 📊
5 habits for sense-checking outputs, via @arjunraj.bsky.social 1/2
It is still mind boggling to think about how quickly that all changed.
A white paper on Stem Cell Based Embryo Models #SCBEM #Innovation #Ethics #Policy, from the community to highlight the potential of this new area of research and its impact in #ReproBiology shorturl.at/dAWL2
I think there are many proposals that would be better than the current system :).
Generally speaking, I don’t think review is an efficient way to make science better.
napari 0.7.0 is available now! 🚀🎉
It's a BIG release so read the full release notes, with highlights: napari.org/stable/relea...
We want to thank everyone who has worked incredibly hard on this release including our 11 new brilliant contributors 🤩 and the community for their support and feedback!
Interesting. Of course the problem is that if someone has methodological issues coming in, they’ll probably also have them later after the review is long gone. The truth is past rigor reflects future rigor more than we care to admit.
Introducing the Anthropic Science Blog. Increasing the pace of scientific progress is a core part of Anthropic’s mission. The Science Blog will feature new research and stories of how scientists are using AI to accelerate their work. Read the intro:
A question for biologists: we often talk about evolutionary novelty. What does “novelty” mean for you? What’s your favorite definition if any? Or just a rule of thumb for what is and isn’t novel.
Honoured and overwhelmed to receive the 2026 Waddington Medal. Science is a team effort, and I've been fortunate to work alongside exceptional people asking hard questions. Thank you to the BSDB and to everyone who has been part of the journey.
bsdb.org/2026/03/24/2...
Untangling mechanisms underlying #CancerDrugResistance www.nature.com/articles/s41... @jess_ljx @arjunraj.bsky.social #Cancer #DrugResistance #TranslationalScience
@mukherja.bsky.social work on RNAPII clusters is in print today: www.nature.com/articles/s41...
Congrats!
TLDR: RNAPII clusters represent transcriptonally engaged molecules at single genes, not super-stochiometric assemblies.
Please check it out and see the the thread below for a summary.
Scientific publishing: Rethinking how research is reviewed and published
Review of how the loss of impact factor affected submissions at eLife - uneven drop across countries, but generally holding up remarkably well and shows a new model is possible
elifesciences.org/articles/110...
Live imaging of macrophages and neutrophils in a transgenic zebrafish larva. Credit to Prof. Anna Huttenlocher Lab @uwmadisonmmi.bsky.social. #ZebrafishZunday 🧪
Thank you!
Interesting! I disagree with this statement: “AI cannot coexist with education — it can only degrade it.” It is far more nuanced than that. AI is a tool that can help and hurt. It moves so fast that coming up with a uniform policy is counterproductive. Either way, it is here and we must engage.
One of my very favorite papers from the lab! Shows that individual cells can learn by forming memories. Amazing work by Jess Li!
A moment of introspection on how much the world has changed during the time between the initial submission and this (hopefully final) revision:
"This paper seems so quaint now"
"Let's think of it as having contributed an important bit of high-quality training data to Opus 4.7"
Claude Code demo, planning another with more details.
Ran an AI coding workshop with the lab. There was a palpable sense of sadness realizing that skills some of us have spent our lives developing (myself included) are a lot less important now. I see the future 100%, but I do think it's important to acknowledge this sense of loss.
ft. Sam Reffsin, Margaret Dunagin, Yael Heyman, @arjunraj.bsky.social (Bioeng), Jesse Miller, Kasirajan Ayyanathan, Sara Cherry (@pennpathlabmed.bsky.social), @naveen-jain.bsky.social (@cambupenn.bsky.social) & David Schultz (BioBio) @penngenetics.bsky.social www.sciencedirect.com/science/arti...
The TIG1-high state exists in human lung club and ciliated cells, enriched in IPF patients and tobacco users. Different viruses target different states. Influenza A prefers KRT8-high cells. Arjun Raj @cp-cell.bsky.social
doi.org/10.1016/j.ce... 🧪
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Reffsin, Miller, Cherry & Raj et al. discover that intrinsic cell states determine which cells become infected with SARS-CoV-2. Using single-cell clone tracing, they identified a TIG1-high state marking highly susceptible cells. What makes these cells vulnerable? 👇🏻
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