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Simona Cocco Directrice de Recherche CNRS Equipe: Physique Statistique et Inference pour la Biologie
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 mail :simona.cocco@phys.ens.fr phone: (33) 1 44323371
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Research Topics: Statistical Physics, Inference and Machine Learning for Biology
De La Physique Statistique Pour Modéliser des Protéines
Book: From Statistical Physics to Data-Driven Modeling with Application to Quantitative Biology. Simona Cocco, Remi Monasson, Francesco Zamponi, Oxford University Press 2022
Tutorial Website
IESC Cargese Summer MOLECULAR EVOLUTION AND DESIGN: from Computational Models and Machine Learning to Biological and Medical Applications
Cargèse, France , August 18-29, 2025
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Softwares
The softwares developed in the group are collected in the Cocco-Monasson github repository.ACE: A fast and flexible code for solving the inverse Ising/Potts inference problem
JP Barton, E. De Leonardis, A. Coucke, S. Cocco
Bioinformatics doi: 10.1093/bioinformatics/btw328 (2016)
ProteinMotifRBM:Learning Protein Constitutive Motifs from Sequence Data: RBM toolbox and PGM
J. Tubiana, S. Cocco, R. Monasson
eLife 2019;8:e39397 (2019). See also the press release.
RBM-MHC: a predictor for class I antigen presentation
B. Bravi, J. Tubiana, S. Cocco, R. Monasson, T. Mora, A.M. Walczak
Cell Systems 12, 1-8 (2021)
Teaching
M2 Course 2022 Machine Learning For Cognitive Sciences: Principles and Applications
M2 Course 2022 Computation and Data Driven Physics
M2 Course 2017-20212020 Inference,Information,Networks: from StatisticalPhysics to `Big’Biological Data
People
Among my collaborators : R. Monasson, J.Marko, D. Chatenay , S. Leibler , M. Barbi , M. Peyrard , M. Weigt, J.Barton, P. Sulc, A. Komarova, C. Nizak, G.Debregeas, D. Hekstra, B. Greenbaum, N. Douarche, V. Baldazzi, C. Barbieri, V. Sessak, G. Tavoni, U. Ferrari, E. de Leonardis, A. Coucke, L. Posani, F.Rizzato,M. Molari, C Roussel, A Di Gioacchino, S. Wolf, J Fernandez de Cossio, E. Mauri,B.Bravi, C. Malbranke, M.Trippa
LPS-ENS, 24, rue Lhomond, Office GH301, 75231 Paris Cedex 05, France.