Aline Marguet

Curriculum vitae

Research interests

• Branching processes, structured populations, growth-fragmentation equations
• Statistical inference for tree-structured data
• Inheritance, noise in gene expression, bacterial communities

Research projects

• ARBOREAL: Branching resource allocation processes for the analysis and inference of phenotypic growth variability (2024-2029), ANR JCJC
• IMOCEP: Innovations en modélisation de la croissance, Projet ciblé  PEPR Maths-Vives (2024-2029)
• AnaComBa: Analysis of bacterial communities: stochastic modelling (2021-2024), Équipe-Action PERSYVAL-lab
• MOSTIC: Stochastic modelling and inference for cell communities in interaction (2020-2022), IXXI

Publications

• A. Marguet, C. Smadi, Spread of parasites affecting death and division rates in a cell population , Stochastic Processes and their Applications, 168, pp.104262, 2024.
• E. Reginato, A. Marguet, E. Cinquemani, Inference of tree-structured auto-regressive models of gene expression parameters from generation-snapshot data, Proceedings of the 22nd European Control Conference, ECC, Stockholm, Sweden, June 25-28, 2024.
• A. Marguet, C. Smadi, Parasite infection in a cell population: role of the partitioning kernel, submitted, arXiv:2305.06962, 2023.
• V. Bansaye, B. Cloez, P. Gabriel, A. Marguet, A non-conservative Harris ergodic theorem, Journal of the London Mathematical Society, 106, 2459-2510, 2022.
• A. Marguet, C. Smadi, Long time behaviour of continuous-state nonlinear branching processes with catastrophes, Electronic Journal of Probability, 26, no. 95, 1-32, 2021.
• A. Marguet, E. Cinquemani. Identification of stochastic gene expression models over lineage trees, Proceedings of the 19th IFAC symposium on System Identification, Padova, July 13-16, 2021.
• A. Marguet, M. Lavielle, E. Cinquemani, Inheritance and variability of kinetic gene expression parameters in microbial cells: Modelling and inference from lineage tree data, Bioinformatics, 35(14), i586–i595, 2019.
• A. Marguet, Uniform sampling in a structured branching population, Bernoulli, 25, 4A, 2649-2695, 2019.
• M. Hoffmann, A. Marguet, Statistical estimation in a randomly structured branching population, Stochastic Processes and their Applications, 129, 12, 5236-5277, 2019.
• A. Marguet, A law of large numbers for branching Markov processes by the ergodicity of ancestral lineages, ESAIM: Probability and Statistics, 23, 638–661, 2019.
• B. Cloez, R. Dessalles, A. Genadot, F. Malrieu, A. Marguet, R. Yvinec, Probabilistic and Piecewise Deterministic models in Biology, ESAIM: Proceedings and Surveys, 60, 225-245, 2017.

PhD students

• Eugène Ferragu, 2024- .
  Co-supervisor: Charline Smadi
• Charles Medous, 2021-2024 , Interacting population, spine construction and stochastic simulations.
  Co-supervisors: Loren Coquille, Charline Smadi
• Emrys Reginato, 2020- , Heterogeneity of microbial populations from stochasticity across cell divisions: individual-based modelling and inference on case studies.
  Co-supervisor: Eugenio Cinquemani.

Courses
2019 – , Biostatistics, M2 Biology, Université Grenoble Alpes

Organizational activities

• Co-organizer of the “Séminaire de modélisation du vivant“
• Member of the scientific committe of GDR Branchement
• Representative of reseachers at “Comité de centre”, Inria centre at the University Grenoble Alpes (2021-2024)
• Member of “Comité” des études doctorales”, Inria centre at the University Grenoble Alpes

top of page