Director, Graduate Program in Bioinformatics and Computational Biology
Department of Pharmacology
- Signal Transduction
- Noise in Gene Expression
- Airway Surface Volume Regulation
- Motor Proteins
A main focus of our laboratory is to use computational and mathematical methods to discover and understand control mechanisms used to regulate signaling pathways. In general, signaling pathways are highly nonlinear and inherently noisy systems. They often contain multiple feedback and feedforward loops and share common functional components. Therefore, the broad questions we seek to address are: What biological functions do feedback and feedforward loops provide? Is noise reduction important for maintaining signaling integrity? How is pathway specificity achieved? To answer these questions, we have chosen to study the mating response pathway of yeast S. cerevisiae. This system is arguably the best- characterized signaling pathway of any eukaryote, and it has long served as a prototype for hormone, neurotransmitter, and sensory response systems in humans. We have developed an interdisciplinary research program that combines computational modeling with experimental analysis. Both deterministic and stochastic models of G-protein and protein kinase activity are being developed and validated against experimental data from the Dohlman Lab. The models are used to generate testable hypotheses that define the next generation of experiments.