Network Inference and Perturbation to Study Chemical-Mediated Cancer Induction

SPRING 2014 RESEARCH INCUBATION AWARDEE

Stefano Monti (Computational Biomedicine, School of Medicine)

The proposed project is aimed at integrating multiple genomic data types (primarily, gene expression and high-throughput “cell painting”) to develop predictive models of chemical carcinogenicity based on network reconstruction and differential analysis approaches, toward the identification of a chemical’s mechanism(s) of cancer induction. The project has a strong computational component, will require the development of novel analytical approaches. It has the potential to transform the field of computational toxicology and the study of chemically-driven tumor initiation.

This work is funded by a Hariri Research Award made in June, 2014.