The Stochastics and Biology Group (SBG), is one of the six research teams of the Probability and Statistics Lab. (LPSM — UMR CNRS 8001) of Sorbonne Université. The French name of SBG is Modélisation Aléatoire du Vivant (MAV). The team was created in 2011 in the former LPMA. SBG is led by G. Nuel since 2018 (A. Lambert former head of SBG, 2011-2017).
SBG gathers probabilists and statisticians of the LPSM interested in mathematical problems inspired by biology and/or applying mathematics to biological problems.
SBG's main biological research themes are:
The SMILE project (Stochastic Models for the Inference of Life Evolution) has been led by Amaury Lambert since 2012. It gathers probabilists, bio-informaticians and biologists forming an autonomous research group hosted by the CIRB (Center for Interdisciplinary Research in Biology) at Collège de France.
The main topics covered by the project are:
Main partners involved:
Main collaborators in Paris: H. Morlon (ENS), R. Ferrière (ENS), S. De Monte (ENS), P. Rainey (ESPCI), V. Courtier-Orgogozo (CNRS), O. Rivoire (CNRS), O. Tenaillon (INSERM), E. Rocha (Pasteur).
Grants: SMILE is supported by Collège de France and CNRS. Salaries of postdocs and PhD students are provided by ANR, LabEx MemoLife, the Ministry of Research via Ecole Normale Supérieure and the IPV doctoral programme of Sorbonne Université.
This project is led by G. Nuel since 2013. The primary objective of this project is to study the genetic factors in important age-dependent diseases like cancer, diabetes or rare genetic diseases. The challenge is to combine state-of-art survival analysis methods in the context of genetic dependence in (possibly large) pedigrees through Bayesian networks.
Our project initially focused on breast and ovarian cancers and BRCA mutations in partnership with Institut Curie. Beside this ongoing collaboration, we work now with Saint-Antoine Hospital on MSI Cancer (Lynch syndrome). This theme of research is one of the two priority axis of the recently obtained SIRIC CURASMUS (Sorbonne Université). SIRIC (sites de recherche intégrée sur le cancer — 7 SIRIC in France) is an excellence from the National Cancer Institute (INCA) to acknowledge a cancer site highly involved in translational research.
In this context, we are are interested in:
Main partners involved:
Grants: INSERM/IRESP DECURION (2013-2016, €120K), LNCC PhD grant (2013-2016, €100K), LNCC PhD grant (2018-2021, €100K), SATT IDF, SIRIC CURASMUS.
Stochastic modeling in Neuroscience has experienced an important development since the last ten years. Our objective is to address this topic with the recent achievements of Probability Theory and Statistics in connexion with our colleagues in computational and/or experimental Neuroscience. We hope that the mathematical approach will help to build simplified but biologically relevant models, to identify small sets of determinant parameters or to single out generic mechanisms that may help practitioners. We use both theory and numerics.
In the team we are interested at the same time in a single neuron and in populations of neurons. At the cell level we have focused on the role of the ion channels on the excitability of the neuron. Ion channels may undergo mutations and a dysfunction in the ion channels may cause pathologies (called channelopathies). Rythmic behaviours are also fundamental, at the cell level as well as for populations. Indeed alteration of natural rythm or emergence of collective periodic behaviour (synchrony) can be associated to neurologic diseases (epilepsy, Parkinson's disease, Alzheimer's disease in particular).
A few mathematical key words relevant for us: Piecewise Deterministic Markov Processes in finite and infinite dimension, stochastic Kuramoto model, synchronization, coupled random oscillators, hypoelliptic diffusions, long time behavior of time dependent multidimensional diffusions, thinning method, parameter estimation, fast-slow systems.
Michèle Thieullen has supervised the PhD theses of Gilles Wainrib (co-direction with K. Pakdaman IMJ Univ. Paris-Diderot), Alexandre Genadot, Vincent Renault (co-directed with Emmanuel Trélat LJLL-UPMC), Alexis Vigot. Currently she is co-supervising together with Vincent Lemaire (LPSM) the PhD Thesis of Nicolas Thomas.
We have benefited from the support of the french National Research Agency (ANR): projet ANR blanc MANDy (2009-2012), coordinator Michèle Thieullen (SBG, LPSM), 23 members, 4 poles: LPSM-UPMC, Univ. of Orléans (around Nils Berglund), INRIA Sophia-Antipolis (around Etienne Tanré), IMJ (Institut Jacques Monod) Univ. Paris-Diderot (around Khashayar Pakdaman). This project MANDy gathered colleagues from Probability Theory, PDE, Dynamical Systems and Computational Neuroscience.
GN is an expert in probabilistic graphical models (e.g. HMMs, Bayesian networks) and computational statistics (e.g. EM algorithm, penalized likelihood). He is interested in a wide range of biomedical applications: tropical disease, bioaccoustics, genetic epidemiology, bioinformatics, clinical research, systems biology, and cancer genetics. Co-head of group since 2018.
AL is professor at Sorbonne Université and at the biology department of Ecole Normale Supérieure. He is a specialist of random trees and of stochastic modeling and statistical inference in population genetics and phylogenetics. He leads the SMILE group, one of the 20 research groups of the Center for Interdisciplinary Research in Biology (CIRB, Collège de France). Former head of the group 2011-2017.
CM is a statistician working at the interface between statistical modeling and life sciences. In particular, she has worked on the statistical analysis of graphs with a focus on ecological networks. Starting 2018, she is partly on leave as deputy director of the national scientific institute of mathematics and their interactions.
ES is a probabilist with expertise in stochastic modeling for population genetics and theoretical ecology. ES is interested in applying results from probability theory (such as branching processes) to understand exchangeable population models, and also to investigate how spatial structure and recombination have shaped the genetic diversity and the ecological composition of extant populations.
MT is a probabilist with expertise in stochastic modeling for Neuroscience. Up to now her research has focused on the role of ion channels in neural excitability through Piecewise Deterministic Markov Processes in finite and infinite dimension. MT is also interested in numerics and estimation problems for these models.
Félix Foutel-Rodier (PhD student) — member
PhD starting Sep 2018, supervised by A. Lambert (SBG, LPSM) and E. Schertzer (SBG, LPSM). Currently doing a six-month internship at Oxford under the supervision of Prof. Alison Etheridge.
Alexandra Lefebvre (PhD student) — member
PhD started in 2018 under the supervision G. Nuel (SBG, LPSM) and A. Duval (INSERM, Saint-Antoine Hospital). With a dual biology-mathematics background, AL is working on Bayesian network and survival analysis with applications in cancer genetics. Funding: Ligue Nationale contre le Cancer.
Nicolas Thomas (PhD student) — member
PhD started in 2014 under the supervision M. Thieullen (SBG, LPSM) and V. Lemaire (LPSM). NT is working on probabilistic numerical methods with applications in Neurosciences.
Originally a physicist, BF has strong interest for mathematical approaches to the dynamics of collective systems. His contributions to modeling in Biology deal with gene regulatory networks, VDJ recombination and allelic exclusion, and populations of synthetic genetic circuits.
SG is a statistician and assistant professor at Paris Diderot University. After a PHD in the field of survival analysis, she had done a post-doctorate in statistical analysis of single cell RNA-Seq data with applications to cancer research. Her actual research mainly focuses on statistical analysis of high dimensional genomic data and applications in biology and medicine.
FV is a statistician and assistant professor at Sorbonne Université. During her PhD in INRA, she worked on statistical models usefull for analysing transcriptomics data. Her main research field is high dimensional statistics and in particular the analysis of network data.
ER has defended his PhD at INRA Jouy-en-Josas and Université Paris Sud in 2007 and is Maître de conférences since 2008 at Université Pierre et Marie Curie (now Sorbonne Université), where he defended his HdR in 2015. His main research field is multiple testing and high dimensional statistics.
OB is an expert in survival analysis, with applications to the biomedical field. His research mainly focuses on new estimation methods for recurrent event data, competing risk/multi state models, interval censoring and new algorithms for detecting heterogeneity in survival analysis. Delegation CNRS (6 months): February-July, 2018.
Vivien Goepp (PhD student, Paris Descartes) — visiting member
VG has a background in engineering and statistics. He is currently interested in models of heterogeneity in survival analysis based on penalized likelihood methods. Visiting SBG from February to July, 2018.
Eric Adjakossa (PhD student) — member
PhD defense in 2017 under the supervision of G. Nuel (SBG, LPSM) and A. Garcia (IRD UMR 216, Paris Descartes).
Ikram Allam (PhD student) — member
PhD defense in 2018 under the supervision of G. Nuel (SBG, LPSM) and A.-C. Camproux (MTi, Paris Diderot).
Alexandre Genadot (PhD student) — member
PhD defense in 2013 under the supervision of M. Thieullen (SBG, LPSM). Funding ED386.
Gilles Monneret (PhD student) — member
PhD started in 2014 under the supervision G. Nuel (SBG, LPSM) and F. Jaffrézic (INRA, Jouy-en-Josas). Defense scheduled in February 2018. Funding: ED386.
Vincent Renault (PhD student) — member
PhD defense in 2016 under the supervision of E. Trélat (LJLL, UPMC) and M. Thieullen (SBG, LPSM). Funding ED386.
Alexis Vigot (PhD student) — member
PhD defense in 2016 under the supervision M. Thieullen (SBG, LPSM).
theme of this year's edition will be "Methods for evolutionary genomics”,
including genome evolution, phylogenomics, population genomics, functional
Deadline for registration: March 3, 2018.
Statistical Methods for Post Genomic Data. The main topics are : Genome conformation, Analysis of biological images, and Causal inference. Deadline for abstract submission: November 30, 2018. Deadline for (free !) registration: January 14, 2019.
cups of coffee drunk
conference talks given
article pages published
Lines of code written