275440 Insilico Multiscale Models for Identifying Driver Versus Passenger Mutations in Cancer Progression
We describe current advances in multiscale computational modeling and simulation approaches in our laboratory combining models in structural biology and those in systems biology. The overall aim is to build quantitative models of signaling networks while retaining the crucial elements of molecular specificity, which appear to be highly relevant to profiling and predictive modeling of clinical mutations in many transformed cell lines. We discuss current and emerging experimental and computational methods, particularly focusing on hybrid and multiscale methods, which we have developed, and highlight several applications in cell signaling with quantitative and predictive capabilities. The scope of such models range from delineating protein-protein interactions to describing clinical implications in the context of mutations in ErbB family receptors (EGFR, HER2, HER3, and HER4) in non-small-cell lung cancer, and ALK receptor in pediatric neuroblastoma.
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