Arjun Krishnan

Our Perspective article on Computational Strategies for Cross-Species Knowledge Transfer is now published in @natmethods.nature.com! This was a collab b/w @krishnanlab.bsky.social & @fishevodevogeno.bsky.social, led by the amazing Hao Yuan @yhbioinfo.bsky.social. 🧵 www.nature.com/articles/s41...

Arjun Krishnan reposted

cell.comRotational settings quantize nucleosome movement by chromatin regulatorsChromatin regulators are thought to override intrinsic DNA sequence preferences. La et al. show regulators move nucleosomes in quantized 10 bp steps to take advantage of the shallow energy potential c...

Chromatin regulators move nucleosomes in 10 bp steps that preserve rotational setting, using the shallow energy potential that DNA sequence creates. www.cell.com/cell-reports... 🧵

Arjun Krishnan reposted

Annika Barber

@annikabarber.bsky.social

Replying to @sbarolo.bsky.social

Really liked this pair of articles about the use of AI in doctoral training from @compbiologist.bsky.social that addresses just these points and how to deal with them. Article: zenodo.org/records/1893... Practical guide to implementation: zenodo.org/records/1845...

zenodo.orgBuild expertise first: why PhD training must sequence AI use after foundational skill developmentGenerative AI tools have arrived in PhD training environments faster than principled frameworks for their use. The debate has polarized between enthusiasts who argue trainees must adopt AI immediately...

Arjun Krishnan reposted

nature.comFragmentation patterns of human telomeric chromatin in plasma cfDNA - Nature CommunicationsTelomeres protect the ends of chromosomes, but their structure has been hard to study non-invasively. Here, the authors show that DNA fragments in blood plasma capture this structure, revealing change...

Fragmentation patterns of human telomeric chromatin in plasma cfDNA www.nature.com/articles/s41...

Srinivas Ramachandran@4everbiochemist.bsky.social

New from the lab: cfDNA provides an unexpected window into telomere chromatin state and genome-wide chromatin changes that accompany telomere shortening, from a blood draw. We hope this opens a path toward monitoring telomere biology disorders with a blood test. www.biorxiv.org/content/10.6...

biorxiv.orgbiorxiv.org

Arjun Krishnan reposted

Casey Dunn

@caseywdunn.bsky.social

25 Aug

My new book, Phylogenetic Biology, is now published. Available online for free at dunnlab.org/phylogenetic... . Physical copies can be purchased at shop.lightningsource.com/b/085?params... or your favorite bookstore.

Arjun Krishnan reposted

Institute for Artificial Intelligence in Medicine

3 June

biorxiv.orgbiorxiv.org

Arjun Krishnan reposted

@iaim-nu.bsky.social

12 May

@nucatsinstitute.bsky.social and @kristiholmes.bsky.social were pleased to host @compbiologist.bsky.social for a seminar discussing his lab's work developing #ComputationalMethods that organize poorly labeled data. The goal is to make millions of publicly available datasets discoverable.

Arjun Krishnan reposted

Ran Blekhman

@blekhman.bsky.social

29 Apr

🧬 AI in Genomics Symposium next week! We're bringing together leading scientists from across academia and industry pushing the boundaries of AI in genomics research Join us May 8 at the University of Chicago - KCBD Auditorium, 9:30–5:00, reception to follow. No registration needed!

compbiologist.substack.comWhat is the PhD actually for?A response to Prachee’s “Free the PhD”, and a critique of my own work

13 Apr

What is the PhD actually for, especially now that AI can do increasingly more of what we train scientists to do? compbiologist.substack.com/p/what-is-th... A response to @pracheeac.bsky.social's thought-provoking essay "Free the PhD".

cu.taleo.netPost-Doctoral FellowClick the link provided to see the complete job description.

7 Apr

Sean Davis & I are hiring a postdoc to work on turning massive public biological data collections into reusable engines for discovery. #ML / #AI + large-scale omics + open software Details + apply: cu.taleo.net/careersectio... seandavi.github.io | thekrishnanlab.org @cubiomedinfo.bsky.social

doi.orgBuild expertise first: why PhD training must sequence AI use after foundational skill developmentGenerative AI tools have arrived in PhD training environments faster than principled frameworks for their use. The debate has polarized between enthusiasts who argue trainees must adopt AI immediately...

6 Apr

A lab using my recent articles on AI use during PhD training doi.org/10.5281/zeno... & doi.org/10.5281/zeno... to kickstart a discussion and draft guidelines for their group is exactly the kind of use I hoped these articles would inspire! Highly recommend reading Ran's post.

Ran Blekhman@blekhman.bsky.social

I wrote about why every lab should have AI use guidelines, and how to do it. open.substack.com/pub/blekhman...

open.substack.comYou need to make AI guidelines for your labHere's why you should, and how to start

Arjun Krishnan reposted

Ran Blekhman

@blekhman.bsky.social

5 Apr

I wrote about why every lab should have AI use guidelines, and how to do it. open.substack.com/pub/blekhman...

open.substack.comYou need to make AI guidelines for your labHere's why you should, and how to start

Arjun Krishnan reposted

Braasch Lab @ Michigan State University

@fishevodevogeno.bsky.social

3 Apr

@compbiologist.bsky.social and @fishevodevogeno.bsky.social present newly minted Dr. Hao Yuan @yhbioinfo.bsky.social! @michiganstateu.bsky.social Amazing work @ the intersection of computational, biomedical, and evolutionary biology! Hao starts a postdoc in the @edwardmarcotte.bsky.social Lab soon.

20 Mar

We have a new platform for employees to give and receive kudos, and it's weekly digests are brutal!

9 Mar

Enjoyed working w/ Stephen & Agnes on this! Gave me a chance to think systematically about where AI 🤖 can backstop human 🧑🏼‍🔬 fallibilities in peer review (fatigue, ordering effects, bias) vs. where human judgment remains essential (novelty, feasibility, creative leaps) while grappling w/ the risks.

Stephen Turner@stephenturner.us

Peer review reliability is shockingly low. Meta-analyses show reviewer agreement barely above chance, and grant outcomes often depend more on who reviews than what's proposed. Our new preprint with Agnes Urban and Arjun Krishnan @compbiologist.bsky.social : papers.ssrn.com/sol3/papers.... 🧵 1/

Arjun Krishnan reposted

PhD programs worldwide face an urgent question: How should trainees use ChatGPT, Claude & similar tools? Now online: two resources on thoughtfully integrating generative AI into research training. 📄 Conceptual framework: zenodo.org/records/18649847 📋 Practical guide: zenodo.org/records/18452319 🧵

zenodo.orgExpertise before augmentation: a practical guide to using generative AI during research trainingThis comprehensive implementation guide accompanies the framework described in "Build expertise first: why PhD training must sequence AI use after foundational skill development" (Krishnan, 2026, DOI:...

7/8 The practical Guide 📋 (zenodo.org/records/18452319) provides task-specific protocols for computational data analysis, manuscript writing, literature review, and more. Designed to be adapted by institutions, programs, and labs for their specific training contexts.

8/8 PhD programs, mentors, & professional societies urgently need community standards built on developmental frameworks, not ad hoc policies shaped by convenience. Thanks to NSF for the support. We welcome feedback from the community to refine these ideas! #PhDLife #Bioinformatics #OpenScience

5/8 The solution is sequencing: Build foundational expertise FIRST through deliberate, feedback-driven practice. Then use AI to augment that expertise. The threshold isn't a fixed number of attempts; it's demonstrated independent mastery: complete tasks, explain reasoning, catch errors.

6/8 The Perspective article 📄 (zenodo.org/records/18649847) presents the conceptual framework grounded in empirical evidence from learning science. It introduces principles like "expertise before augmentation" and explains why cognitive automation during training undermines development.

3/8 The key insight: GenAI is categorically different from previous automation (calculators, statistical software, search engine). Those automated mechanical execution. GenAI automates cognition itself: reasoning, synthesis, judgment. This difference changes everything about when it should be used.

4/8 We introduce the "verification paradox": trainees can't meaningfully verify AI outputs because verification requires the very expertise they're still developing. Using AI before that expertise exists bypasses the developmental process while producing polished outputs that mask the gap.

news.cuanschutz.eduCU Anschutz Recruits National Leader to Launch Functional Personalized Medicine InitiativeCU Anschutz welcomes Alice Soragni to launch a Functional Personalized Medicine Initiative using rapid tumor organoid testing to guide treatment decisions.

2/8 The debate has polarized between "adopt now or fall behind" vs "AI will destroy learning." Both miss the critical question: not WHETHER ❓ to use AI, but WHEN ⏳.

Arjun Krishnan reposted

Stephen Turner

@stephenturner.us

16 Feb

From Arjun Krishnan @compbiologist.bsky.social Expertise before augmentation: a practical guide to using generative AI during research training: zenodo.org/records/1845... Build expertise first: why PhD training must sequence AI use after foundational skill development: zenodo.org/records/1864...

Arjun Krishnan reposted

Soragni:Lab

@alice.soragnilab.com

10 Feb

Happy to share this new, very intentional chapter. I have left UCLA after 14 years to join the University of Colorado Anschutz as Professor of Biomedical Informatics and Neurosurgery and the inaugural Marsico Chair in Excellence in Functional Precision Medicine/n news.cuanschutz.edu/dbmi/cu-ansc...

Arjun Krishnan reposted

Braasch Lab @ Michigan State University

@fishevodevogeno.bsky.social

26 Jan

Our Fish EvoDevoGeno Lab @michiganstateu.bsky.social has its 10th anniversary today! 🐠🐟🧪🧬🔬 Thanks to all lab members - present & past, pictured or not - for making the last decade a success! & thanks to our partners in crime of the @brainyfishguts.bsky.social Lab, too! #EndlessFishMostBeautiful

I'm looking forward to re-teaching: Rethinking Data Analysis — A researcher’s guide to avoiding missteps and misuse This is an advanced short course on developing a mental toolkit for rigorous practice & critical consumption of statistical data analyses. 🧵 1/4

3/4 As a result, most students piece together a mental model of acceptable, standard, or "best" practices in their field from shards of information gathered from mentors, peers, and published papers.

4/4 This advanced short course formalizes the instruction of these ideas. The goal is to: 1) Discuss common misunderstandings & typical errors in the practice of statistical data analysis. 2) Provide a mental toolkit for critically thinking about statistical methods & results. Feedback welcome 🙌🏼

nature.comComputational strategies for cross-species knowledge transfer - Nature MethodsThis Perspective reviews computational methods for cross-species knowledge transfer and introduces ‘agnology’, a data-driven concept of functional equivalence independent of evolutionary origin.

2/4 Statistical inquiry, data analysis, and visualization are immensely powerful, but many of the ideas underlying them are nuanced and unintuitive. Unfortunately, these ideas—and the skills needed to apply them to real problems and datasets—are rarely taught in statistics or data-analysis courses.

Arjun Krishnan reposted

Nature Methods

@natmethods.nature.com

18 Dec 2025

A Perspective reviews computational methods for cross-species knowledge transfer. www.nature.com/articles/s41...

9/10 By embracing data-driven, evolution-agnostic approaches, we believe that the field can accelerate discoveries in both common and rare diseases, improving model organism selection and ultimately paving the way for more reliable therapeutic interventions.

10/10 Big thanks to NIH/NIGMS, NSF, & @simonsfoundation.org for funding this work! We welcome feedback from the community! 🙌 #Bioinformatics #TranslationalResearch #OpenScience

7/10 Kudos to resources like @geneontology.bsky.social , @monarchinitiative.bsky.social, @alliancegenome.bsky.social, & @bgee.org for grounding so much data & knowledge in this space in structured formats. These & many others are included in our catalog ☝🏽

8/10 Key future directions we highlight: - Capturing specific facets of complex diseases - Building networks for more species & contexts - Automated ontology/knowledge graph construction - Better benchmarking for cross-species single-cell methods - Leveraging non-traditional research organisms

5/10 With the explosion of large-scale multi-species genomics data and advanced #AI & #ML methods, it's an exciting time to rethink cross-species translational biomedicine. Our article offers a roadmap to navigate this frontier and maximize the value of research organisms.

6/10 We provide detailed resources to help computational & wet-lab researchers find, improve-upon, and apply appropriate methods: 📊 Supp Table 1: Comprehensive catalog of methods (name, category, input/output, data types) 📚 Supp Table 2 & Note: Valuable datasets for cross-species work

3/10 Our article covers methods that tackle 4 key questions in cross-species research: 1. Predicting function/disease-gene relationships across species 2. Identifying agnologous molecular components 3. Inferring perturbed transcriptomes across species 4. Mapping agnologous cell types and states

4/10 Traditional approaches rely heavily on homology. But shared ancestry ≠ shared function & vice-versa. Here, we introduce the concept of Agnology, which embraces this complexity: "agno-" = unknown/not known, reflecting data-driven functional equivalence regardless of evolutionary origin.

2/10 #ResearchOrganisms like 🐭 & 🐟 are crucial for studying genes, functions, cell types, & disease. But translating findings to 👨‍⚕️ is tricky. We explore data-driven methods to bridge the gap & introduce the concept of "agnologs" — functional equivalents identified independent of evolutionary origin.

Arjun Krishnan reposted

@rnabiologist.bsky.social

16 Dec 2025

Known for decades: DNA sequence drives nucleosome "rotational positioning" (which face of DNA contacts histones) But: How does this persist when remodelers & transcription constantly mobilize nucleosomes? Our new preprint 1/ : www.biorxiv.org/content/10.6...

biorxiv.orgbiorxiv.org

Arjun Krishnan reposted

Suja Jagannathan

21 May 2025

This preprint is now out after peer review! Check it out: www.cell.com/cell-genomic.... Huge congrats (and thanks!) to the whole team that contributed!

cell.comSystematic analysis of nonsense variants uncovers peptide release rate as a novel modifier of nonsense-mediated mRNA decayKolakada et al. discover that the amino acid preceding a premature termination codon influences nonsense-mediated mRNA decay efficiency. They identify peptide release rate during translation terminati...

Suja Jagannathan@rnabiologist.bsky.social

Excited to share the latest work from the lab, led by Divya Kolakada, the first PhD from our group 🎓🤓🎉 Peptidyl-tRNA hydrolysis rate influences the efficiency of nonsense-mediated mRNA decay www.biorxiv.org/content/10.1...

Arjun Krishnan reposted

Kelly Sullivan

@kellydsullivan.bsky.social

14 Feb 2025

Very proud to be a member of this team. A huge group effort to improve the lives of those with Down syndrome. Thank you to everyone that has helped us along the way.

CU Anschutz Linda Crnic Institute for Down Syndrome@crnicinstitute.bsky.social

The Linda Crnic Institute for Down Syndrome is proud to announce that we have been awarded the 2025 Research Collaboration Award at the 2025 @cuanschutz.bsky.social Research Awards! This award recognizes a team for outstanding contributions in research collaborations.

cell.comIntegration of 168,000 samples reveals global patterns of the human gut microbiomeThe Human Microbiome Compendium is a unified database of publicly available human gut microbiome 16S samples, built with the integrated data from hundreds of independent projects. The compendium is us...

22 Jan 2025

Congratulations! Kudos to @richabdill.com & @samanthagraham.bsky.social for leading this huge project! Thanks for bring us onboard! Mansooreh Ahmadian & Parker Hicks lead the part of the work on inferring study annotations from unstructured metadata and text from the linked publications.

Ran Blekhman@blekhman.bsky.social

Today we report a new compendium of human gut microbiomes with >168,000 samples By analyzing this massive dataset, we discovered distinct microbiome patterns across the globe, and show we can predict where a person lives just from their gut bacteria Now out in Cell: www.cell.com/cell/fulltex...