Computational Systems Biology

The Computational Systems Biology Cluster emphasizes the integration of molecular, cellular and inter-cellular processes to achieve understanding about how biological systems (including molecular networks, cells, organs and organisms) operate. Such studies rely on computational methods to analyze and integrate data, construct models and simulate the activity of biological systems. A systems approach to biological research is an iterative process that involves identification of the genes and proteins involved in a biological system, characterization of the molecular interactions that underlie the function of the system, and data-driven modeling that integrates networks of gene and protein interactions to develop simulations of the system. Such simulations give rise to predictions about changes in function when the system is perturbed, which, in turn, leads to experimental testing of these hypotheses, refinement of hypotheses, further modeling and further testing. Identification and functional characterization of gene products has far-reaching implications for mechanistic understanding of biological processes as simple as a molecular reaction and as complicated as animal and human health and disease. Such knowledge will lead to development of gene-based interventions to alter function or tools for disease prevention and therapeutics.