Peter Koo
@pkoo562.bsky.social
AI4Science researcher. Associate Professor @CSHL. My lab advances AI for genomics and healthcare!
http://koo-lab.github.io
http://koo-lab.github.io
Pinned
Peter Koo
@pkoo562.bsky.social
· Oct 9
Which mutations rewire function of regulatory DNA?
Excited to share SEAM: Systematic Explanation of Attribtuion-based Mechanisms. SEAM is an explainable AI method that dissects cis-regulatory mechanisms learned by seq2fun genomic deep learning models.
Led by @EESetiz
1/N 🧵👇
Excited to share SEAM: Systematic Explanation of Attribtuion-based Mechanisms. SEAM is an explainable AI method that dissects cis-regulatory mechanisms learned by seq2fun genomic deep learning models.
Led by @EESetiz
1/N 🧵👇
Reposted by Peter Koo
New online! Decoding the regulatory genome with large-scale deep learning
Decoding the regulatory genome with large-scale deep learning
Nature Reviews Genetics, Published online: 03 November 2025; doi:10.1038/s41576-025-00914-2In this Journal Club, Peter Koo reflects on the 2021 publication of Enformer and its impact on the use of deep learning for modelling the regulatory genome.
www.nature.com
November 3, 2025 at 1:07 PM
New online! Decoding the regulatory genome with large-scale deep learning
Beware of LLM blindspots. #AI4Science
November 8, 2025 at 9:24 PM
Beware of LLM blindspots. #AI4Science
Reposted by Peter Koo
Yijie Kang (CSHL, Stony Brook) from @pkoo562.bsky.social Lab presented "Decoding the sequence basis of Pol II elongation with deep learning"
November 7, 2025 at 3:05 PM
Yijie Kang (CSHL, Stony Brook) from @pkoo562.bsky.social Lab presented "Decoding the sequence basis of Pol II elongation with deep learning"
Exciting symposium on AI and Biology at EMBO | EMBL in Heidelberg on 10-13 March 2026!
Excellent lineup of invited speakers across various scales of biology!
Deadline for abstract submission is coming up — Dec 2.
🔗 www.embl.org/about/info/c...
#EESAIBio @EMBLEvents
Excellent lineup of invited speakers across various scales of biology!
Deadline for abstract submission is coming up — Dec 2.
🔗 www.embl.org/about/info/c...
#EESAIBio @EMBLEvents
November 7, 2025 at 12:16 AM
Exciting symposium on AI and Biology at EMBO | EMBL in Heidelberg on 10-13 March 2026!
Excellent lineup of invited speakers across various scales of biology!
Deadline for abstract submission is coming up — Dec 2.
🔗 www.embl.org/about/info/c...
#EESAIBio @EMBLEvents
Excellent lineup of invited speakers across various scales of biology!
Deadline for abstract submission is coming up — Dec 2.
🔗 www.embl.org/about/info/c...
#EESAIBio @EMBLEvents
Which mutations rewire function of regulatory DNA?
Excited to share SEAM: Systematic Explanation of Attribtuion-based Mechanisms. SEAM is an explainable AI method that dissects cis-regulatory mechanisms learned by seq2fun genomic deep learning models.
Led by @EESetiz
1/N 🧵👇
Excited to share SEAM: Systematic Explanation of Attribtuion-based Mechanisms. SEAM is an explainable AI method that dissects cis-regulatory mechanisms learned by seq2fun genomic deep learning models.
Led by @EESetiz
1/N 🧵👇
October 9, 2025 at 12:03 PM
Which mutations rewire function of regulatory DNA?
Excited to share SEAM: Systematic Explanation of Attribtuion-based Mechanisms. SEAM is an explainable AI method that dissects cis-regulatory mechanisms learned by seq2fun genomic deep learning models.
Led by @EESetiz
1/N 🧵👇
Excited to share SEAM: Systematic Explanation of Attribtuion-based Mechanisms. SEAM is an explainable AI method that dissects cis-regulatory mechanisms learned by seq2fun genomic deep learning models.
Led by @EESetiz
1/N 🧵👇
Congratulations to John Clarke, Michel Devoret and John Martinis on receiving the 2025 Nobel Prize in Physics!
www.nobelprize.org/prizes/physi...
I have fond memories of my time in the Clarke lab, where I did my Honors Thesis on ultra low-field MRI w/ SQUIDs as an undergrad at UC Berkeley!
www.nobelprize.org/prizes/physi...
I have fond memories of my time in the Clarke lab, where I did my Honors Thesis on ultra low-field MRI w/ SQUIDs as an undergrad at UC Berkeley!
October 7, 2025 at 2:16 PM
Congratulations to John Clarke, Michel Devoret and John Martinis on receiving the 2025 Nobel Prize in Physics!
www.nobelprize.org/prizes/physi...
I have fond memories of my time in the Clarke lab, where I did my Honors Thesis on ultra low-field MRI w/ SQUIDs as an undergrad at UC Berkeley!
www.nobelprize.org/prizes/physi...
I have fond memories of my time in the Clarke lab, where I did my Honors Thesis on ultra low-field MRI w/ SQUIDs as an undergrad at UC Berkeley!
Check out a Research Highlights on our work at @naturemethods by Lin Tang!
www.nature.com/articles/s41...
www.nature.com/articles/s41...
September 19, 2025 at 4:36 PM
Check out a Research Highlights on our work at @naturemethods by Lin Tang!
www.nature.com/articles/s41...
www.nature.com/articles/s41...
Richard Bonneau giving the last keynote on navigating the complexity of drug discovery and their lab-in-the-loop for molecule design! #MLCB
September 11, 2025 at 5:40 PM
Richard Bonneau giving the last keynote on navigating the complexity of drug discovery and their lab-in-the-loop for molecule design! #MLCB
September 10, 2025 at 1:52 PM
2025 Machine Learning in Computational Biology (#MLCB) meeting starts TODAY (9/10) at 9:30a (EST) at the NY Genome Center in NYC!
We have a great lineup of keynotes, contributed talks, and posters today and tomorrow
Schedule: mlcb.org/schedule
Join for free via livestream: m.youtube.com/@mlcbconf
We have a great lineup of keynotes, contributed talks, and posters today and tomorrow
Schedule: mlcb.org/schedule
Join for free via livestream: m.youtube.com/@mlcbconf
MLCB - Schedule
The in-person component will be held at the New York Genome Center, 101 6th Ave, New York, NY 10013. All times below are Eastern Time.
mlcb.org
September 10, 2025 at 11:42 AM
2025 Machine Learning in Computational Biology (#MLCB) meeting starts TODAY (9/10) at 9:30a (EST) at the NY Genome Center in NYC!
We have a great lineup of keynotes, contributed talks, and posters today and tomorrow
Schedule: mlcb.org/schedule
Join for free via livestream: m.youtube.com/@mlcbconf
We have a great lineup of keynotes, contributed talks, and posters today and tomorrow
Schedule: mlcb.org/schedule
Join for free via livestream: m.youtube.com/@mlcbconf
*Easter egg alert* NOT in the published paper. We also benchmarked Evo 2 and while it did better than other gLMs (consistent that scale can improve gLMs), it still falls short of a basic CNN trained using one-hot sequences and far short of supervised SOTA
Our work on "Evaluating the representational power of pre-trained DNA language models for regulatory genomics" led by @AmberZqt with help from @NiraliSomia & @stevenyuyy is finally published in Genome Biology! Check it out!
genomebiology.biomedcentral.com/articles/10....
genomebiology.biomedcentral.com/articles/10....
Evaluating the representational power of pre-trained DNA language models for regulatory genomics - Genome Biology
Background The emergence of genomic language models (gLMs) offers an unsupervised approach to learning a wide diversity of cis-regulatory patterns in the non-coding genome without requiring labels of ...
genomebiology.biomedcentral.com
July 16, 2025 at 12:16 PM
*Easter egg alert* NOT in the published paper. We also benchmarked Evo 2 and while it did better than other gLMs (consistent that scale can improve gLMs), it still falls short of a basic CNN trained using one-hot sequences and far short of supervised SOTA
Our work on "Evaluating the representational power of pre-trained DNA language models for regulatory genomics" led by @AmberZqt with help from @NiraliSomia & @stevenyuyy is finally published in Genome Biology! Check it out!
genomebiology.biomedcentral.com/articles/10....
genomebiology.biomedcentral.com/articles/10....
Evaluating the representational power of pre-trained DNA language models for regulatory genomics - Genome Biology
Background The emergence of genomic language models (gLMs) offers an unsupervised approach to learning a wide diversity of cis-regulatory patterns in the non-coding genome without requiring labels of ...
genomebiology.biomedcentral.com
July 16, 2025 at 12:12 PM
Our work on "Evaluating the representational power of pre-trained DNA language models for regulatory genomics" led by @AmberZqt with help from @NiraliSomia & @stevenyuyy is finally published in Genome Biology! Check it out!
genomebiology.biomedcentral.com/articles/10....
genomebiology.biomedcentral.com/articles/10....
Reposted by Peter Koo
One thing that really bothers me with the new "virtual cell" terminology is that it is currently largely focused on a very narrow definition of models that can predict effects of trans perturbations (gene dosage, drugs etc) on gene expression. 1/
June 28, 2025 at 10:38 AM
One thing that really bothers me with the new "virtual cell" terminology is that it is currently largely focused on a very narrow definition of models that can predict effects of trans perturbations (gene dosage, drugs etc) on gene expression. 1/
Reposted by Peter Koo
Excited to launch our AlphaGenome API goo.gle/3ZPUeFX along with the preprint goo.gle/45AkUyc describing and evaluating our latest DNA sequence model powering the API. Looking forward to seeing how scientists use it! @googledeepmind
June 25, 2025 at 2:29 PM
Excited to launch our AlphaGenome API goo.gle/3ZPUeFX along with the preprint goo.gle/45AkUyc describing and evaluating our latest DNA sequence model powering the API. Looking forward to seeing how scientists use it! @googledeepmind
Reposted by Peter Koo
This a really exciting leap forward for genomic sequence to activity gene regulation models. It is a genuine improvement over pretty much all SOTA models spanning a wide range of regulatory, transcriptional and post-transcriptional processes. 1/
Excited to launch our AlphaGenome API goo.gle/3ZPUeFX along with the preprint goo.gle/45AkUyc describing and evaluating our latest DNA sequence model powering the API. Looking forward to seeing how scientists use it! @googledeepmind
June 25, 2025 at 4:18 PM
This a really exciting leap forward for genomic sequence to activity gene regulation models. It is a genuine improvement over pretty much all SOTA models spanning a wide range of regulatory, transcriptional and post-transcriptional processes. 1/
Congrats @avsecz.bsky.social! Looking forward to exploring what it has learned! 🧬
Excited to launch our AlphaGenome API goo.gle/3ZPUeFX along with the preprint goo.gle/45AkUyc describing and evaluating our latest DNA sequence model powering the API. Looking forward to seeing how scientists use it! @googledeepmind
June 25, 2025 at 5:41 PM
Congrats @avsecz.bsky.social! Looking forward to exploring what it has learned! 🧬
Reposted by Peter Koo
@pkoo562.bsky.social Peter Koo at #AIxBio
June 23, 2025 at 11:07 AM
@pkoo562.bsky.social Peter Koo at #AIxBio
Reposted by Peter Koo
With contributions from fantastic colleagues @martinsteinegger.bsky.social , @mikeinouye.bsky.social, @jlistgarten.bsky.social , @ideasbyjin.bsky.social, @michael-heinzinger.bsky.social, and many more, the first CSHL volume on ML for Protein Science and Engineering is out: lnkd.in/dQdgGPpp
June 15, 2025 at 11:30 AM
With contributions from fantastic colleagues @martinsteinegger.bsky.social , @mikeinouye.bsky.social, @jlistgarten.bsky.social , @ideasbyjin.bsky.social, @michael-heinzinger.bsky.social, and many more, the first CSHL volume on ML for Protein Science and Engineering is out: lnkd.in/dQdgGPpp
The #MLCB deadline has been extended to June 3 (AOE)! Still time to submit your cutting-edge work on machine learning in biology. Don’t miss out! 👉 www.mlcb.org #ComputationalBiology #ML4Bio
MLCB
The 20th Machine Learning in Computational Biology (MLCB) meeting will be a two-day hybrid conference, September 10-11, 9am-5pm ET, with the in-person component at the New York Genome Center, NYC. Reg...
www.mlcb.org
June 2, 2025 at 12:26 PM
The #MLCB deadline has been extended to June 3 (AOE)! Still time to submit your cutting-edge work on machine learning in biology. Don’t miss out! 👉 www.mlcb.org #ComputationalBiology #ML4Bio
Building virtual cells is a great goal in the age of AI, but it requires far more than training transformers with scRNAseq.
*Scaling* as the primary strategy with hopes of emergent properties is lazy.
Will the plan to fuse representations across mediocre (unimodal) foundation models work?!
*Scaling* as the primary strategy with hopes of emergent properties is lazy.
Will the plan to fuse representations across mediocre (unimodal) foundation models work?!
May 28, 2025 at 4:39 PM
Building virtual cells is a great goal in the age of AI, but it requires far more than training transformers with scRNAseq.
*Scaling* as the primary strategy with hopes of emergent properties is lazy.
Will the plan to fuse representations across mediocre (unimodal) foundation models work?!
*Scaling* as the primary strategy with hopes of emergent properties is lazy.
Will the plan to fuse representations across mediocre (unimodal) foundation models work?!
Reposted by Peter Koo
Awesome paper. Simple post-hoc trick (averaging over homologs) with elegant evolution theory dramatically improves zero shot coding variant effect prediction in pLMs & actually delivers better results from the larger models (inverting the trend with raw likelihoods). 1/
From Likelihood to Fitness: Improving Variant Effect Prediction in Protein and Genome Language Models https://www.biorxiv.org/content/10.1101/2025.05.20.655154v1
May 26, 2025 at 9:40 AM
Awesome paper. Simple post-hoc trick (averaging over homologs) with elegant evolution theory dramatically improves zero shot coding variant effect prediction in pLMs & actually delivers better results from the larger models (inverting the trend with raw likelihoods). 1/
Excited to share an update to D3 (DNA Discrete Diffusion) — an application of score-entropy discrete diffusion model for regulatory genomics!
🧬 Paper: biorxiv.org/content/10.110…
(See thread below 👇) (1/n)
🧬 Paper: biorxiv.org/content/10.110…
(See thread below 👇) (1/n)
May 23, 2025 at 1:52 PM
Excited to share an update to D3 (DNA Discrete Diffusion) — an application of score-entropy discrete diffusion model for regulatory genomics!
🧬 Paper: biorxiv.org/content/10.110…
(See thread below 👇) (1/n)
🧬 Paper: biorxiv.org/content/10.110…
(See thread below 👇) (1/n)
Reposted by Peter Koo
My sympathy and support for all the international students and postdocs at Harvard. I can only imagine how scary this must feel. Stay strong. And if there's anything I can do to help those in compbio, please reach out. All of us need to rally to help them out. 1/
May 23, 2025 at 10:01 AM
My sympathy and support for all the international students and postdocs at Harvard. I can only imagine how scary this must feel. Stay strong. And if there's anything I can do to help those in compbio, please reach out. All of us need to rally to help them out. 1/
The premier conference on Machine Learning for Computational Biology is Sep 9-10 at the NY Genome Center in NYC!
Submission deadline is June 1 for 2-page abstracts and 8-page papers (eligible for proceedings track).
Registration is now open! (Link below)
Please retweet!
Submission deadline is June 1 for 2-page abstracts and 8-page papers (eligible for proceedings track).
Registration is now open! (Link below)
Please retweet!
May 16, 2025 at 11:26 AM
The premier conference on Machine Learning for Computational Biology is Sep 9-10 at the NY Genome Center in NYC!
Submission deadline is June 1 for 2-page abstracts and 8-page papers (eligible for proceedings track).
Registration is now open! (Link below)
Please retweet!
Submission deadline is June 1 for 2-page abstracts and 8-page papers (eligible for proceedings track).
Registration is now open! (Link below)
Please retweet!