Elias Ventre

Research interest

My work falls within the broader category of mechanistic generative modeling: calibrating mechanistic models of cellular dynamics, in particular parameterized by Gene Regulatory Networks (GRNs), from single-cell data. More specifically:

• Multiscale analysis of stochastic hybid processes,
• Inferring Gene Regulatory Networks from single-cell datasets,
• Cell trajectory reconstruction from single-cell datasets using entropy minimization problems.

Recently, these approaches have found a particularly important application in the analysis of data from patient-derived organoids, in particular for rare pediatric cancers, for which databases are only just emerging and make the use of large, data-hungry AI models poorly suited. In this context, I collaborate with members of the Southrock consortium, at the CRCM and the CRCL.