Constraint-based Causal Structure Learning with Consistent Separating Sets. - Honghao Li; Vincent Cabeli; Nadir Sella; Hervé Isambert (NeurIPS, 2019)

Learning clinical networks from medical records based on information estimates in mixed-type data. - Vincent Cabeli; Louis Verny; Nadir Sella; Guido Uguzzoni; Marc Verny; Hervé Isambert (PLoS Comput. Biol., 2020)

Learning causal graphs from continuous or mixed datasets of biological or clinical interest. (Apprentissage de graphes causaux à partir de données continues ou mixtes d'intérêt biologique ou clinique). - Vincent Cabeli (2021)

Interactive exploration of a global clinical network from a large breast cancer cohort. - Nadir Sella; Anne-Sophie Hamy; Vincent Cabeli; Lauren Darrigues; Marick Laé; Fabien Reyal; Hervé Isambert (npj Digit. Medicine, 2022)

Learning interpretable causal networks from very large datasets, application to 400, 000 medical records of breast cancer patients. - Marcel da Câmara Ribeiro-Dantas; Honghao Li; Vincent Cabeli; Louise Dupuis; Franck Simon; Liza Hettal; Anne-Sophie Hamy; Hervé Isambert (CoRR, 2023)

PyDESeq2: a python package for bulk RNA-seq differential expression analysis. - Boris Muzellec; Maria Telenczuk; Vincent Cabeli; Mathieu Andreux (Bioinform., 2023)