@paulvilloutreix.bsky.social
We develop machine learning frameworks to decode the geometry and topology of tissue development from spatial omics data | Junior Professor INSERM & Group Leader Turing Center for Living Systems | https://bioml.lis-lab.fr
📣 New review! Dynamical systems and low-dimensional geometric structures in phase space help rationalize how embryos develop form and function, from large datasets. We focus on morphogenesis, cell differentiation, and their interconnection.
@alex-plum.bsky.social
sciencedirect.com/science/arti...
Very happy to share video of 1st lecture @college-de-france.fr on Biological computation 😊. I defend the necessity to access Algorithmic & Computational levels of analysis in cell & developmental biol. proposed by David Marr in neuroscience. Logic & Function matter 🤩.
Video: tinyurl.com/55yejk5f
Are you passionate about the mathematics of data science, computational geometry and topology and want to apply your skills to a beautiful biological question?
Come do a PhD with us!
You will help us understand of how boundaries are established and maintained in early heart development.
... and the application process: centuri-livingsystems.org/centuri-phd-...
If you want to develop new quantitative methods, collaborate across disciplines, and work on an exciting biological problem, we’d love to hear from you!
You will join the collaborative, interdisciplinary environment of the Turing Centre for Living Systems (CENTURI) in Marseille, working within the teams of Paul Villoutreix and Robert Kelly!
The full project: centuri-livingsystems.org/wp-content/u...
Are you passionate about the mathematics of data science, computational geometry and topology and want to apply your skills to a beautiful biological question?
Come do a PhD with us!
You will help us understand of how boundaries are established and maintained in early heart development.
Felix Zhou's u-Segment3D is out:
www.nature.com/articles/s41...
It leverages 2D cell segmentations from orthoviews to generate a ‘consensus’ 3D segmentation.
It does a great job on segmenting densely packed samples, and we have used the algorithm in many applications.
Congrats Baptiste on the PhD and a beautiful paper !
academic.oup.com/nar/article/...
Congratulations to Dr @baalberti.bsky.social !! 🎉
And many thanks to his jury members @randersson.bsky.social @arnausebe.bsky.social @olivier-gandrillon.mastodon.social.ap.brid.gy Marie Sémon Anouck Necsulea and co-supervizor @paulvilloutreix.bsky.social
Excited to be in Paris later this week!
09.11.2025 09:37 — 👍 2 🔁 0 💬 0 📌 0
#Agenda
With
@batistaruan.bsky.social, Valentin Rineau, @ignacioq.bsky.social, Aleksandra Walczak, Guillaume Achaz, @k4tj4.bsky.social - @r3rto.bsky.social, Maël Montévil, @paulvilloutreix.bsky.social, Barbara Bravi, Cyril Rauch, Giuseppe Longo, Anton Robert, @charbelelhani.bsky.social , Ana Soto
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
Great program, amazing scientists and beautiful facilities!! I visited for 6 months in 2023, a unique place in Europe at the intersection of maths, computer science and developmental biology
31.10.2025 13:46 — 👍 4 🔁 1 💬 0 📌 0
🧬 Excited to share Nicheformer out now in Nature Methods!
A transformer foundation model linking single-cell & spatial omics, learning spatial context from gene expression to map tissue organization.
Led by Ale Tejada & Anna Schaar 👏
👉 www.nature.com/articles/s41...
Thrilled to share my main postdoc work with @jamesbriscoe.bsky.social
We used genomic barcoding + scRNAseq in chick & human embryos to reveal a lineage architecture that reshapes how we understand neural tube development & cell fate decisions
🧵👇
www.biorxiv.org/content/10.1...
Had a very nice time visiting Granada for the annual heart ICDAR meeting! We presented Harshit Pateria's current work in collaboration with Robert Kelly following up from our recent publication on the second heart field www.nature.com/articles/s41...
17.10.2025 15:51 — 👍 4 🔁 1 💬 0 📌 0Wow @gioelelamanno.bsky.social & @giodang.bsky.social
16.10.2025 07:09 — 👍 12 🔁 2 💬 0 📌 0
Pleasure to announce the program of my new series of lectures at the College de France in Nov-Dec. Continuing on the theme of Biological information. I will focus on the computational aspects, building on David Marr's tri-level of analysis in biological systems. YouTube link sent when it starts.
07.10.2025 06:12 — 👍 34 🔁 11 💬 1 📌 0
🤩👍🏼💪🏼 Meet #TopoSPAM - a high-performance simulation platform for biological morphogenesis with a friendly Python interface. @tudresden.bsky.social @csbdresden.bsky.social @mpi-cbg.de. Solve both continuous and discrete active mechanics! Released today: arxiv.org/abs/2509.24905
01.10.2025 10:21 — 👍 18 🔁 6 💬 1 📌 0Very elegant and efficient methodology to recover spatial patterns from multi-modal spatial datasets 👌!! Many congratulations @paulvilloutreix.bsky.social and to all authors👏😀!!
19.09.2025 09:16 — 👍 3 🔁 1 💬 0 📌 0
Link to the preprint ->
www.biorxiv.org/content/10.1...
jsPCA is simple, it is based on the product between the gene expression covariance (classical PCA) and the spatial autocorrelation.
We have shown that it's fast, interpretable and highly adaptable to multiple settings and large datasets.
Congrats to Ines Assali who led the project!
We came up with an initial formulation of jsPCA last year when studying single cell morphometrics data
www.nature.com/articles/s41...
which was build on sPCA www.nature.com/articles/hdy....
To adapt it to spatial transcriptomics, we had to leverage sparsity and non convex optimization on manifold.
Finally, principal components of jsPCA are directly interpretable in terms of spatially variable genes (SVG). We found that the top 3000 genes of the first principal component recovered 80% of the SVGs obtained by the widely used SPARK-X method.
19.09.2025 06:49 — 👍 0 🔁 0 💬 1 📌 0
jsPCA can also learn a joint representations on some of the slices and use it to predict the domains in an unseen slice.
19.09.2025 06:49 — 👍 0 🔁 0 💬 1 📌 0
The joint analysis of multiple slices by jsPCA generates common domains among datasets, in contrast to monoslice analysis..
19.09.2025 06:49 — 👍 0 🔁 0 💬 1 📌 0
jsPCA achieves state-of-the-art accuracy for domain identification while reducing computation from hours to seconds, and scales to atlas-level datasets such as Stereo-seq.
19.09.2025 06:49 — 👍 0 🔁 0 💬 1 📌 0
Very happy to introduce jsPCA, a fast and interpretable computational framework for spatial transcriptomics that simultaneously identifies spatial domains and variable genes across multi-slice and multi-sample data.
19.09.2025 06:49 — 👍 17 🔁 8 💬 2 📌 0
hoxd13a reporter in a zebrafish larva
Are digits modified fins, or evolutionary innovations? Read how we tackled this old question from a new angle🧪
A story with @chasebolt.bsky.social, @homeobox.bsky.social and myself, coordinated by @denisduboule.bsky.social from @college-de-france.fr and published in @nature.com today!
#InHoxWeTrust
This work was motivated by settings with scarce data such as rare diseases.
It turned into multi-dimensional puzzles and alignement problems that we really enjoyed solving! Congrats to Daniel Lepe-Soltero, the postdoc who led this work.
Link -> arxiv.org/abs/2503.18856
