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 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
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
The conference talks are online at legend2025.sciencesconf.org/data/book_le...
The conference talks are online at legend2025.sciencesconf.org/data/book_le...
www.nature.com/articles/d41...
www.nature.com/articles/d41...
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
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
Logan now democratizes efficient access to the world’s most comprehensive genetics dataset. Free and open.
doi.org/10.1101/2024...
Logan now democratizes efficient access to the world’s most comprehensive genetics dataset. Free and open.
doi.org/10.1101/2024...
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.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!
➡️ www.ins2i.cnrs.fr/fr/cnrsinfo/...
🤝 @lisnlab.bsky.social @cnrs-paris-saclay.bsky.social
➡️ www.ins2i.cnrs.fr/fr/cnrsinfo/...
🤝 @lisnlab.bsky.social @cnrs-paris-saclay.bsky.social
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...
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...
The 580€ include housing and all meals.
We will close on October 17th or when reaching 80 participants.
Mark your calendars and make sure your best work is ready next September when the call for abstracts opens 🙂
legend2025.sciencesconf.org
The 580€ include housing and all meals.
We will close on October 17th or when reaching 80 participants.
probgen2026.github.io
Please help spread the news.
probgen2026.github.io
Please help spread the news.
À lire sur le blog #FocusSciences🎯 du CNRS 👉 lejournal.cnrs.fr/nos-blogs/fo...
academic.oup.com/mbe/advance-...
The thread below provides a summary of our neural network for likelihood-free phylogenetic reconstruction.
academic.oup.com/mbe/advance-...
The thread below provides a summary of our neural network for likelihood-free phylogenetic reconstruction.
Mark your calendars and make sure your best work is ready next September when the call for abstracts opens 🙂
legend2025.sciencesconf.org
Mark your calendars and make sure your best work is ready next September when the call for abstracts opens 🙂
legend2025.sciencesconf.org
academic.oup.com/bioinformati...
Let's break it down:
academic.oup.com/bioinformati...
Let's break it down:
A blog post to celebrate and present it: francisbach.com/my-book-is-o...
A blog post to celebrate and present it: francisbach.com/my-book-is-o...
go.bsky.app/73rcuJn
go.bsky.app/73rcuJn
Faster than distance methods like neighbor joining, it outperforms maximum likelihood methods under complex models of sequence evolution.
🧵
Faster than distance methods like neighbor joining, it outperforms maximum likelihood methods under complex models of sequence evolution.
🧵
Keynotes by Sara Mathieson, Hélène Morlon, Pier Palamara and Tal Pupko.
Register and submit your abstract here: legend2024.sciencesconf.org
Keynotes by Sara Mathieson, Hélène Morlon, Pier Palamara and Tal Pupko.
Register and submit your abstract here: legend2024.sciencesconf.org