ErbB signaling pathways are among the best studied mammalian signaling networks, and involved in cell proliferation, survival and motility. Their dysregulation has been implicated in a variety of human cancers, and ErbB receptors and downstream targets are a major focus of current pharmaceutical research. Peter Sorger of Harvard Medical School has been involved in modeling ErbB pathways for over a decade and has expertise in the collection and analysis of dynamic multi-factorial data, using a variety of approaches including high throughput micro-ELISA assays, flow cytometry, and fixed and live-cell imaging combined with perturbations by RNAi and small-molecule drugs.

As a member of the Center for Multiscale Analysis of Genomic and Cellular Networks, Sorger is co-leading a project with Dennis Vitkup to conduct probabilistic dynamic modeling of the ErbB signaling pathways. The goal of the project is to understand the core biological processes controlling the ErbB pathways, including identifying key proteins implicated in ErbB signal transduction in cancer cell lines, discovering core biochemical parameters controlling ErbB network signaling, and making probabilistic predictions describing likely network perturbations. The model prediction will be tested and refined using either RNAi or small-molecule perturbations.