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Our lab develops predictive models of cell metabolism, protein expression, and gene regulation. Specifically, we develop holistic models that integrate multiple biological processes and large-scale networks. Interpreting biological data in the context of these integrated models provides a systems-level perspective on cellular functions.

Our lab trains systems biologists from two angles. First, trainees will learn to express their biological knowledge and intuition in the form of computable, mathematical models. These models then provide an in silico platform to virtually test hypotheses and to design efficient experiments. Second, researchers have ample opportunity to deploy machine learning and distributed algorithms on big biological data sets. These algorithms can improve the accuracy of model predictions, or to help understand biological mechanisms by constructing explainable models from data.

Laurence is the Project Leader for the Open Plastic.