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Vito Quaranta, M.D.

Professor, Biochemistry & Pharmacology
Director, Quantitative and Chemical Biology Program

Systems-level models of cancer drug response & transcription factor networks

Cancer Systems Biology is the definition of our mixed experimental and theoretical approach to studying many aspects of cancer progression, including invasion, metastasis, resistance to drugs, effects of mutations. Rather than focusing on clarifying details of a molecular or genetic pathway, or specific effects of growth or differentiation factors or proteases or drugs, we try and combine these details into a global picture that specifies overall trends in growth and progression of specific cancer cells under distinct microenvironmental conditions. Thus, we build quantitative hypotheses that translate experimental observations or datasets into computer simulations based of several mathematical modeling techniques, including ordinary or partial differential equations, cellular automata, neural networks, immersed boundary method.