Computational genomics, computational systems biology, and applications of machine learning to biology
The Brent Lab is developing and applying mathematical and computational methods for mapping gene regulation networks, modeling them quantitatively, and synthesizing new network designs in living cells. Michael Brent and his team 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.
Professor Brent believes 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 his team to a number of projects in which molecular experiments are driven by predictive models.
After completing his PhD in Computer Science at MIT, Professor Brent served as Assistant and Associate Professor of Cognitive Science at the Johns Hopkins University, where his research focused on computational modeling of how children learn language.
He brought these interests to Washington University in St. Louis in 1999, where he developed a second research program in computational biology and eventually phased out computational linguistics. From 2001 to 2008 he focused on computational and molecular methods for improving the accuracy of genome annotation. Since 2008, Professor Brent has focused on computational and molecular methods for mapping and modeling gene regulation networks.
Professor Brent was elected Fellow of the American Association for the Advancement of Science (AAAS) in 2012.