Laurent Jacob
@laurentjacob.bsky.social
Researcher in statistics and machine learning for genomics https://laurent-jacob.github.io/
I’m also recruiting a postdoc to work on an NSF-funded project focused on using machine learning for population genetic inference. Would love to talk to anyone who is interested! (Official ad to come soon).
Megan Smith@snaildit.bsky.social · 2mo agoThe lab is en route to #Evol2026! We’ve got several talks:
🌎 🧬 🖥️ logan-search.org the tool to query all SRA sequences (Dec 2023 snapshot) — just got major updates. Here's what's new. 🧵 1/12
The video recordings of the legend 2025 conference held last December on machine learning for evolutionary genomics are now online ! Feel free to have a look if you missed the conference. www.canal-u.tv/chaines/lisn...
Hello all, we are looking for PhD candidates. Details are in the document below. Please feel free to spread the word. Thank you!
Excited to announce a new 5-year project on developing generative models for complex trait genomics. I’m now looking for PhD candidates with CS, ML, stats or bioinformatics backgrounds. I’d very much appreciate it if you could spread the word. Contact: burak.yelmen@ut.ee
We're organising a microbes & deep learning session at SMBE next year -- looking forward to seeing your abstracts!
Society for Molecular Biology and Evolution@official-smbe.bsky.social · 8mo agoOrganisers - @bacpop.org | @embl.org - @aweimann.bsky.social | University of Cambridge Invited Speaker - @audeber.bsky.social | Institut Pasteur
legend 2025 will be next Tuesday/Wednesday/Thursday. The detailed program is on legend2025.sciencesconf.org?lang=en If you are not attending the conference you can still follow the presentations online (Zoom links are on the website).
legend2025 : Machine Learning for Evolutionary Genomics Data - Sciencesconf.org
Evolutionary genomics and population genetics investigate patterns of genetic diversity between species or between populations within a species and play a fundamental role in many aspects, from theoretical facets of evolution to practical ones, such as conservation genetics and biomedical sciences.
legend2025.sciencesconf.org
Laurent Jacob@laurentjacob.bsky.social · last yr.The next LEGEND conference on machine learning for evolutionary genomics will be in Aussois (French Alps) between December 8th and 12th. Mark your calendars and make sure your best work is ready next September when the call for abstracts opens 🙂 legend2025.sciencesconf.org
Happy to share STORIES out now on Nature Methods STORIES learns cell fate landscapes from spatial tramscripromics data profiled at several time points, thus allowing prediction of future cell states. Led by Geert-Jan Huizing and Jules Samaran www.nature.com/articles/s41... @pasteur.fr
STORIES: learning cell fate landscapes from spatial transcriptomics using optimal transport - Nature Methods
By learning a differentiation potential using an optimal transport-based approach, STORIES models and infers cell fate trajectories using spatiotemporal omics data.
nature.com
Very happy about this work on phylogenetic neural inference, led by @lblassel.bsky.social :)
Luc Blassel@lblassel.bsky.social · 10mo agoWe’re very excited to finally share our latest work: Phyloformer 2, a deep end-to-end phylogenetic reconstruction method: arxiv.org/abs/2510.12976 Using neural posterior estimation, it outperforms Phyloformer 1 and maximum-likelihood methods under simple and complex evolutionary models. 🧵1/17
October 17 is your last chance to register for the 2nd conference on Machine Learning for Evolutionary Genomics Data (Dec 8-12), in the French Alps at legend2025.sciencesconf.org The conference talks are online at legend2025.sciencesconf.org/data/book_le...
legend2025 : Machine Learning for Evolutionary Genomics Data - Sciencesconf.org
Evolutionary genomics and population genetics investigate patterns of genetic diversity between species or between populations within a species and play a fundamental role in many aspects, from theoretical facets of evolution to practical ones, such as conservation genetics and biomedical sciences.
legend2025.sciencesconf.org
Ca n'est pas si souvent, un article publié dans Nature met ma communauté à l'honneur (la bioinformatique des séquences). Je vous raconte ? www.nature.com/articles/d41...
‘Google for DNA’ brings order to biology’s big data
MetaGraph compresses vast data archives into a search engine for scientists, opening up new frontiers of biological discovery.
nature.com
The decisions for LEGEND are out: legend2025.sciencesconf.org/data/book_le... I'm really looking forward to hearing these 21 exciting presentations (and additional 30 posters) next December. If you want to attend too, registration is open until October 17th through legend2025.sciencesconf.org
![Exploring the space of self-reproducing RNA using generative models, Martin Weigt
Exploring the archaic introgression landscape of admixed populations through
joint ancestry inference, Jazeps Medina Tretmanis [et al.]
Predicting natural variation in the yeast phenotypic landscape with machine
learning, Sakshi Khaiwal [et al.]
Phylodynamic modeling with unsupervised Bayesian neural networks, Marino
Gabriele [et al.]
Likelihood-free inference of phylogenetic tree posterior distributions, Luc Blas-
sel [et al.]
Generative continuous time model reveals epistatic signatures in protein evolu-
tion, Barrat-Charlaix Pierre
Neural posterior estimation for high-dimensional genomic data from complex pop-
ulation genetic models, Jiseon Min [et al.]
A differentiable model for detecting diversifying selection directly from alignments
in large-scale bacterial datasets, Leonie Lorenz [et al.]
Detecting interspecific positive selection using transformers, Charlotte West [et al.]
Predicting Multiple Sequence Alignment Uncertainty via Machine Learning, Lucia
Martin-Fernandez [et al.]
Graph Neural Networks for Likelihood-Free Inference in Diversification Mod-
els, Amélie Leroy [et al.]
Popformer: learning general signatures of genetic variation and natural selection
with a self-supervised transformer, Leon Zong [et al.]](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:7x5c6ifrcznmg4mzhfuc2a6r/bafkreidur7bz43o2jhwr4gbt36awozawqthbkkfeszxjkxf4kvhyh7q6du)
![PRIVET: PRIVacy metric based on Extreme value Theory, Antoine Szatkownik [et
al.]
Generative models for inferring the evolutionary history of the malaria vector
Anopheles gambiae, Amelia Eneli [et al.]
Language Models Outperform Supervised-Only Approaches for Conserved Ele-
ment Comprehension, Eyes Robson [et al.]
Identification and Classification of Orphan Genes, Spurious Orphan Genes, and
Conserved Genes from the human microbiome, Chen Chen
Neural Simulation-based inference of demography and selection, Francisco De
Borja Campuzano Jiménez [et al.]
Species Identification and aDNA Read Mapping Using k-mer Embeddings, Filip
Thor [et al.]
Contrastive Learning for Population Structure and Trait Prediction, Filip Thor [et
al.]
Protein and genomic language models chart a vast landscape of antiphage de-
fenses, Mordret Ernest
The Phylogenomics and Sparse Learning of Trait Innovations, Gaurav Diwan [et
al.]](https://cdn.bsky.app/img/feed_thumbnail/plain/did:plc:7x5c6ifrcznmg4mzhfuc2a6r/bafkreig4akadduemzbit67bv7jnr7x2ircwiriykabg2imuf3phy6hhube)
Only a few hours left to submit your abstract for a talk at the Machine Learning in Evolutionary Genomics conference in December in Aussois in the French alps!
#MLCB2025 is tomorrow & Thursday with a fantastic lineup of keynotes & contributed talks www.mlcb.org/schedule. We'll be livestreaming through our YouTube channel www.youtube.com/@mlcbconf. Thanks to www.corteva.com, instadeep.com, the Simons Center at CSHL & NYGC for generous support!
MLCB - Schedule
The in-person component will be held at the New York Genome Center, 101 6th Ave, New York, NY 10013.
mlcb.org
Achievement unlocked: defend your habilitation thesis on the same day than your partner. That was quite a science + celebration day, thanks to all involved 💙✨
🌎👩🔬 For 15+ years biology has accumulated petabytes (million gigabytes) of🧬DNA sequencing data🧬 from the far reaches of our planet.🦠🍄🌵 Logan now democratizes efficient access to the world’s most comprehensive genetics dataset. Free and open. doi.org/10.1101/2024...
The call for abstract for LEGEND is now open: legend2025.sciencesconf.org It will close on September 22nd (oral presentations) and October 1st (posters). Send us your best work on Machine Learning for Evolutionary Genomics and come discuss it with us in the French Alps next December!
legend2025 : Machine Learning for Evolutionary Genomics Data - Sciencesconf.org
legend2025.sciencesconf.org
Laurent Jacob@laurentjacob.bsky.social · last yr.The next LEGEND conference on machine learning for evolutionary genomics will be in Aussois (French Alps) between December 8th and 12th. Mark your calendars and make sure your best work is ready next September when the call for abstracts opens 🙂 legend2025.sciencesconf.org
#TalentCNRS 🥉| Flora Jay, entre génomes synthétiques et récits évolutifs, reçoit la médaille de bronze du CNRS. ➡️ www.ins2i.cnrs.fr/fr/cnrsinfo/... 🤝 @lisnlab.bsky.social @cnrs-paris-saclay.bsky.social
Preprint alert! 🦌 Our new abundance index, REINDEER2, is out! It's cheap to build and update, offers tunable abundance precision at kmer level, and delivers very high query throughput. Short thread! www.biorxiv.org/content/10.1... github.com/Yohan-Hernan...
biorxiv.org
Registration is now open! The 580€ include housing and all meals. We will close on October 17th or when reaching 80 participants.
Laurent Jacob@laurentjacob.bsky.social · last yr.The next LEGEND conference on machine learning for evolutionary genomics will be in Aussois (French Alps) between December 8th and 12th. Mark your calendars and make sure your best work is ready next September when the call for abstracts opens 🙂 legend2025.sciencesconf.org
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.
Home - ProbGen 2026
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probgen2026.github.io
Merci à @cnrs-rhoneauvergne.bsky.social et @astropierre.com pour cette interview sur mes travaux en IA pour la génomique évolutive!
CNRS Rhône Auvergne@cnrs-rhoneauvergne.bsky.social · last yr.Grâce à l’IA, les scientifiques disposent de nouveaux outils pour décrypter, analyser et interpréter les milliards de lettres de notre ADN🧬. Explications de Laurent Jacob chercheur en IA pour la génomique au #CQSB À lire sur le blog #FocusSciences🎯 du CNRS 👉 lejournal.cnrs.fr/nos-blogs/fo...
Phyloformer is finally published in MBE! 🎉 academic.oup.com/mbe/advance-... The thread below provides a summary of our neural network for likelihood-free phylogenetic reconstruction.
Phyloformer: Fast, accurate and versatile phylogenetic reconstruction with deep neural networks
Abstract. Phylogenetic inference aims at reconstructing the tree describing the evolution of a set of sequences descending from a common ancestor. The high
academic.oup.com
Laurent Jacob@laurentjacob.bsky.social · 2y agoWe just released a preprint for Phyloformer, a likelihood-free inference method for phylogenetic reconstruction: biorxiv.org/content/10.1... Faster than distance methods like neighbor joining, it outperforms maximum likelihood methods under complex models of sequence evolution. 🧵
The next LEGEND conference on machine learning for evolutionary genomics will be in Aussois (French Alps) between December 8th and 12th. Mark your calendars and make sure your best work is ready next September when the call for abstracts opens 🙂 legend2025.sciencesconf.org
🧬 Excited to share our latest work, MUSET 🌭, a new tool for creating abundance unitig matrices from sequencing data. It was published yesterday in Oxford Bioinformatics if you want to have a look👀 : academic.oup.com/bioinformati... Let's break it down:
MUSET: Set of utilities for constructing abundance unitig matrices from sequencing data
AbstractSummary. MUSET is a novel set of utilities designed to efficiently construct abundance unitig matrices from sequencing data. Unitig matrices extend
academic.oup.com
My book is (at last) out, just in time for Christmas! A blog post to celebrate and present it: francisbach.com/my-book-is-o...
Ok, I tried to create my own list of people working on developing statistical or machine learning models applied to omics data. I am sure I missed a lot of cool people. If you'd like to be added, let me know. #Stats #ML #Omics go.bsky.app/73rcuJn
We just released a preprint for Phyloformer, a likelihood-free inference method for phylogenetic reconstruction: biorxiv.org/content/10.1... Faster than distance methods like neighbor joining, it outperforms maximum likelihood methods under complex models of sequence evolution. 🧵
The first LEGEND conference on Machine Learning for Evolutionary Genomics will be held on May 13-15th in Heraklion! Keynotes by Sara Mathieson, Hélène Morlon, Pier Palamara and Tal Pupko. Register and submit your abstract here: legend2024.sciencesconf.org