Jeffrey Chuang is Professor at the Jackson Laboratory for Genomic Medicine, where he leads a computational lab investigatingproblems at the intersection of cancer, evolution, and image analysis. He obtained his Ph.D. in physics from MIT before switching into computational biology for a postdoc at UCSF.His leadership positions include serving as PI for the NCI Cancer Moonshot Patient-Derived Xenograft Network Data Commons and Coordination Center, co-PI for the NCI Pediatric Cancer In Vivo Testing Consortium Coordination Center, co-Research Program Leader and interim Deputy Director of the JAX Cancer Center and faculty advisor for the JAX Computational Sciences core.
Broad advances in sequencing, imaging, and machine learning are rapidly transforming the nature of biology research, providing rich avenues for discovery at the nexus of experimentation, mechanistic modeling and neural network analysis. My lab uses computational, mathematical, and high-throughput data generation approaches to study how cancer ecosystems function, evolve, and respond to therapeutic treatment. We study problems in cancer sequence and image analysis across a wide spectrum of cancer types, with particular expertise in breast cancer and patient-derived xenografts.