A primary goal of cancer systems biology is to build models of cell regulatory systems that can predict the impact of genetic changes that cause cancer and that can be used to design therapeutic strategies. Unfortunately, the great majority of current signaling models are mostly descriptive and lack the ability to predict responses across different cell types or the impact of gene copy number alterations. To address this critical capability gap, we have developed a measurement-modeling-perturbation ...

Poster presented at the 2019 annual CSBC meeting: A major aim of cancer systems biology is to build models that can predict the impact of these genetic disruptions to guide therapeutic interventions. A prominent driver of cancer cell growth is signaling pathway deregulation from mutations in key regulatory nodes and loss/gain in gene copy number (CNV). Recent work by our group discovered that the abundances of most signaling pathway proteins are highly conserved with signaling being controlled ...