Joint Computational Science Center/Biology Department Seminar

Systems biology is likely to have a great impact on the biological sciences in the future. For example, whole genome sequencing, DNA microarrays and proteomics are providing information that can be used to reconstruct cellular networks. However, in order to fully exploit these data, we must develop mathematical and computational methods to interpret and predict the behavior of cellular networks. In this talk, I will describe our computational techniques for elucidating metabolic network behavior and receptor dynamics. In the first part of the talk I will discuss a constraints based approach for determining the flux distribution in metabolic networks without the requirement of kinetic parameters. I will also demonstrate how we have been able to utilize this approach to study the adaptation of metabolic networks, which has potential applications in metabolic engineering. Next, I will discuss our work with the ErbB receptors, which are dysregulated in a high proportion of cancers and a critical target for anti-cancer drugs. Despite a plethora of biochemical studies and recent single particle tracking experiments, the molecular mechanisms involving ligand binding and dimerization are not well understood. I will describe a spatially distributed Monte Carlo based simulation framework to enable the simulation of in vivo receptor diffusion and dimerization. Our simulation results are in agreement with the data from single particle tracking and biochemical experiments on ErbB receptors. Overall, in this talk I will show that simulations of biological systems can be used to gain a mechanistic understanding of cellular function.