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How do computational methods reveal interactions and dynamics in complex biological systems across time? The Systems Biology Group develops computational methods for understanding interactions, dynamics and conservation of complex biological systems using approaches that span experimental design to systems-level analysis. The group builds algorithms inspired by biological distributed systems to improve distributed computing and to infer information-processing principles in biology. Projects include development of methods for experimental design and for reconstruction of dynamic biological networks from high-throughput temporal data. Researchers apply machine learning and bioinformatics to integrate static and temporal datasets to model biological system behavior.
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