Machine Learning
Partial label learning for automated classification of single cell transcriptomic profiles
Malek Senoussi, Thierry Artieres*, Paul Villoutreix* – PLoS Computational Biology
Hierarchical classification for weakly supervised transcriptomics data
Malek Senoussi, Thierry Artieres, Paul Villoutreix – CAp, 2022
Cross-View Kernel Transfer
Riikka Huusari, Cécile Capponi, Paul Villoutreix, Hachem Kadri – Pattern Recognition, 2022
What can machine learning do for developmental biology
Paul Villoutreix, invited paper, Development, 2021
Towards a general framework for spatio-temporal transcriptomics
Julie Pinol, Thierry Artières, Paul Villoutreix, NeurIPS LMRL workshop, 2020
Synthesizing developmental trajectories
Paul Villoutreix*, Joakim Andén*, Bomyi Lim, Hang Lu, Yannis Kevrekidis, Amit Singer, Stanislav Y. Shvartsman – PLoS Comput Biol 13(9): e1005742, 2017.
Biologically informed modeling
Random walk informed heterogeneity detection reveals how the lymph node conduit network influences T cells collective exploration behavior
Solène Song, Malek Senoussi, Paul Escande, Paul Villoutreix – PLoS Computational Biology 2023, in press
Entropic effects in cell lineage tree packings
Jasmin Imran Alsous*, Paul Villoutreix*, Norbert Stoop*, Stanislav Y. Shvartsman, Jörn Dunkel – Nature Physics, 14(10), 1016-1021, 2018
Collective Growth in a Simple Cell Network
Jasmin Imran Alsous, Paul Villoutreix, Alexander M. Berezhkovskii, Stanislav Y. Shvartsman – Current Biology 27(17), 2670–2676, 2017.
Single cell morphometrics
Single-cell morphometrics reveals T-box dependent patterns of epithelial tension in the Second Heart field
Submitted
Application of 3D MAPs pipeline identifies the morphological sequence chondrocytes undergo and the regulatory role of GDF5 in this process
Sarah Rubin, Ankit Agrawal, Johannes Stegmaier, Jonathan Svorai, Yoseph Addadi, Paul Villoutreix*, Tomer Stern*, Elazar Zelzer* – Nature Communications, 2021
Video explaining the main findings : http://vimeo.com/463129275
An integrated modelling framework from cells to organism based on a cohort of digital embryos
Paul Villoutreix*, Julien Delile*, Barbara Rizzi*, Louise Duloquin*, Thierry Savy, Paul Bourgine, René Doursat, Nadine Peyriéras, Scientific Reports, 6:37438, 2016.
Code and Datasets or github repository
Book Chapter
Vers une modélisation multi-échelle de la variabilité biologique?
Paul Villoutreix, Chap. 19 in Modéliser & Simuler. Epistémologies et pratiques de la modélisation et de la simulation. Tome 2, Franck Varenne, Marc Silberstein, Philippe Huneman et Sebastien Dutreuil, Eds. pp. 643 – 664, Editions matériologiques, Novembre 2014.
Ph.D Thesis
Randomness and variability in animal embryogenesis, a multi-scale approach
Paul Villoutreix, PhD Dissertation – Université René Descartes – Paris V, 2015
Others
Piece of news on the Embryo Project Encyclopedia.
Showcase on the Information is Beautiful Award website.
Blog post describing The Embryo Digital Atlas’ journey to the Global Sprint.
Interview on Mozilla Science Lab blog – The Embryo Digital Atlas.
Blog post discussing our work on data-driven visualizations of developing embryos and its relationships to art. This is a supporting webpage for Mozilla Science Lab community call on art and science.