Presentation

SIMBA (Statistical Inference and Modeling for Biological Applications) is a joint Inria, Université de Lorraine and CNRS project-team, hosted at the Institut Élie Cartan de Lorraine (IECL), the Mathematics Laboratory of the Université de Lorraine. It is a team of researchers in mathematics applied to biology and medicine, with a wide range of expertise in statistical and stochastic modeling and methods, for applications and in collaboration with researchers from INRAE, CHRU Nancy and Strasbourg, Institut de Cancérologie de Lorraine, etc.

We specialize in stochastic processes, multi-scale structured population dynamics models, their scaling limits in different biologically motivated regimes (large population, mean-field asymptotics, slow-fast averaging, long time behavior…) and their numerical simulation. Our expertise in statistics covers various aspects of statistical learning and regression (variable selection, goodness-of-fit…), streaming data analysis, change point detection, network models (e.g. for gene networks) and inference for classes of processes important in biology, such as piecewise deterministic Markov processes.

Among the team’s main applications, we are interested in oncology in modeling tumor growth, inferring tumor heterogeneity from genetic data, and building decision support tools for tumor evolution. We study the evolution of telomere lengths in humans and other organisms such as yeast and corals. We are interested in stochastic gene expression in connection with the analysis of single-cell transcriptomic data. We are also applying our models to epidemiology, in particular plant epidemiology, with the study of the French invasion of an ash tree disease, chalara.