Dr. David Klinke, West Virginia University
Monday, April 6 12:00PM, TRC, Rm 206
A Bayesian Perspective on Understanding Cell Signaling Pathways using Mathematical Models
Cellular response to extracellular stimuli is governed by biochemical reactions that allow the transfer of information from the cell membrane to the nucleus and back. The integrity of this mechanism for information processing is attributed to a series of dynamic protein-protein interactions. Decades of scientific scrutiny have revealed the molecular players in many cellular signaling networks. Yet how these molecular players create a dynamic flow of information – by interacting in space, in time, and in specific systems – remains relatively unknown. Our lab focuses on combining aspects of chemical kinetics, Bayesian inference, and proteomics to quantify the functional consequences of genetic variation. The functional consequences of interest give rise to differences in the flow of information within cellular signaling pathways. Our approach will be illustrated using two examples. To provide a context for these examples, I will provide a semi-biased review the current state-of-the-art in analyzing cell signaling pathways using mathematical models. The first example focuses on understanding differences in signaling pathways among cellular models of breast cancer. The second example focuses on understanding the regulation of Interleukin-12 signaling within naïve CD4+ T cells.