Centers & Programs

Center for Computational Systems Biology

Motivation and Activities

In a sense, contemporary systems biology is a renaissance of physiology, a traditional integrative discipline. Biological research has enjoyed decades of success in dissecting the structures and functions of individual molecular and cellular components comprising an organism. However, the inherent complexity of biological systems, due not only to the large number of their constituents, but also to the intricate web of interactions between these constituents, have proven difficult to understand with reductionist approaches. Research has to be conducted at a more global, systems-level in order to gain understanding of the overall behavior of the biological networks that maintain normal physiology and the perturbations in these networks that lead to toxicity and disease. Environmental stressors, including physical and chemical agents, exert adverse effects by initially impinging on specific molecular or cellular targets. Responses arising from the initial interactions propagate along the normal molecular, cellular or systemic networks, ultimately affecting the health of the intact organism. Our applications of computational systems biology in risk assessment focuses on developing quantitative simulation models of the dose-response relationships for network perturbations by chemical stressors.

Computational Systems Biology

One essential component of our systems biology research effort is the integration of computational modeling with laboratory research in order to link conventional intuitive modeling with more formal mathematical modeling of biological processes affected by chemical exposures (see schematic above). In silico simulation is routinely employed in physics, chemistry, and engineering. Biological research has made less use of these modeling tools, due to lack of data to characterize molecular and cellular networks and to the lack of familiarity of many biologists with tools for this type of quantitative analysis. With improvement of the high-data content 'omic' tools for mapping the "nuts and bolts" of biological systems, computational modeling of signaling networks is now feasible and will be essential for gaining functional insight into these biological processes.

Through using a variety of modeling techniques, Center for Computational Systems Biology staff focus on developing mechanistic simulation models that are specially customized for evaluating biological consequences of the interactions of chemical and physical agents with biological systems. The Center promotes incorporation of biologically based modeling at the earliest feasible stages of laboratory research projects, including experimental design, data interpretation, and hypothesis testing.

Future Courses

Computational Systems Biology and Dose Response Modeling Workshop, to be offered September 2008. Details coming soon.

Affiliated Scientists

Postdoctoral Fellows

Predoctoral Fellows

  • Rebecca Clewell