Causal Networks and Applications to Molecular Biology

Abstract

While causal graph discovery seems appealing for biological data analysis, these approaches have had limited impact on single-cell and molecular data analysis. We examine three key barriers: restrictive assumptions in causal models, scalability limitations, and identifiability challenges in real biological datasets. In this overview, we discuss these obstacles, highlighting recent progress as well as emerging opportunities.

Romain Lopez

Assistant Professor of Computer Science and Biology

My research interests lie at the intersection of statistics, computation and modeling of biological data. A significant part of my research is driven by building more statistically accurate and faster machine learning software for analyzing genomics data.