Computational identification and quantitative modeling of dynamic cellular pathways

The ability of cells to carry out life functions arises from the collective behavior of interacting molecules. Cells are able to integrate multiple internal and external messages simultaneously and respond reliably with a predefined set of outcomes. This adaptability and robustness is based on a complex system of signaling and regulatory molecules, which interact in dynamic circuits to regulate and support all aspects of cell growth and function. James Taylor brings a background in engineering physics to the study of molecular biological systems. He is using mathematical and computational modeling to simulate information flow through dynamic molecular circuits. In parallel, he is designing microfluidic platforms for the experimental testing of these circuits on the single cell level. James hopes to increase the efficiency of biological discovery and the use of predictive modeling in drug discovery. Employing filamentous form cell differentiation in yeast as a model system, he is characterizing the dynamics of a new circuit within the MAP Kinase cascade, a common signaling system that plays a central role in integrating the signals from a diverse group of external stimuli to regulate processes such as cell proliferation, cell differentiation, cell movement and cell death. Using a double headed approach of modeling and experimentation, he is continuing to research how this complex circuit enables the cell to robustly integrate multiple internal and external molecular messages simultaneously.