Research
Overview
The Brent Lab is developing and applying mathematical/computational methods for mapping gene regulation networks, modeling them quantitatively, and synthesizing new network designs in living cells. We are driven by the conviction that probabilistic and dynamical systems modeling need not be merely a theoretical or descriptive exercise - predictive models can be applied now in ways that impact our daily choice of experiments to carry out and enable a deeper, systems level understanding of how gene regulation interacts with cellular physiology. We believe that modeling is most useful when it guides experiments in a tight feedback loop. Models of transcriptional regulatory networks have their greatest impact when constructed for the purpose of explaining how specific physiological outcomes are regulated. And synthetic regulatory circuits are most interesting when they are interfaced to meaningful cellular physiology. The drive to apply mathematical and computational methods to complex, biologically meaningful problems has led us to a number of projects in which molecular experiments are driven by predictive models. Some of these projects are described below.
