Personalized Cancer Therapies using Genomic Information


We propose a novel graph-based optimization approach to modeling gene regulatory networks for the purpose of understanding gene interactions and pathway function in the presence of mutations. This formulation allows for the assessment of pathway disruption and provides biological insight into the optimal drug targets for a given mutation profile. Empirical results suggest that this approach recovers biologically valid relationships between genes. We extend work by Bertsimas and Zhuo to incorporate this structured pathway model and demonstrate recovery of new drug-target interactions.

Practice-Oriented Session
INFORMS Healthcare 2019