Description
Date depot: 5 avril 2021
Titre: Causal network analysis of single cell multi-omics data applied to a cellular therapy against multiple sclerosis
Directeur de thèse:
Hervé ISAMBERT (PC_Curie)
Directeur de thèse:
Simon FILLATREAU (Institut Necker)
Domaine scientifique: Sciences et technologies de l'information et de la communication
Thématique CNRS : Non defini
Resumé: This PhD project aims at extending a recent causal network learning method from the Isambert lab (Institut Curie) to analyze single cell multi-omics data obtained by the Fillatreau lab (Institut Necker) during an innovative cellular therapy against multiple sclerosis, an autoimmune disease of the central nervous system that disrupts the flow of information within the brain and between the brain and body. The Isambert lab has previously developed an unsupervised causal structure learning method combining the analysis of multivariate information with novel interpretable constraint-based graphical models. In this project, we will extend this early machine learning approach for non-temporal datasets to analyze time-resolved longitudinal multi-omics data (scRNAseq/ATACseq). Analyzing temporal information about cellular interaction dynamics is expected to facilitate the discovery of novel time-delayed regulatory processes between different cell types implicated in this promising cellular therapy against multiple sclerosis.
Doctorant.e: Dupuis Louise Raymonde Berthe