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
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.