Ph.D., University of New Mexico, 2009
Postdoctoral Research: Broad Institute
Lab website: http://pages.discovery.wisc.edu/~sroy
Address: 3168 Wisconsin Institutes for Discovery
Department: Biostatistics and Medical Informatics
Research InterestsMachine learning methods to study the structure, function and evolution of regulatory networks and build predictive models.
Research FieldsComputational, Systems & Synthetic Biology
Evolutionary & Population Genetics
Human, mouse & rat
Our research focuses on developing statistical computational methods to identify the networks driving cellular functions by integrating different types of genome-wide datasets, that measure different aspects of the cellular state. We are interested in identifying networks under different environmental, developmental and evolutionary contexts, comparing these networks across contexts, and constructing predictive models from these networks. This can help us understand (1) how environmental information is processed in cells to mount appropriate condition-specific responses, (2) how these networks change across different contexts such as environmental stresses, cell-types, tissues, diseases, and, (3) how these networks have evolved to suit organism life-style and habitat. Most important, by comparing such networks across many different contexts, we can identify the general organizational principles as well as notable exceptions that underlie condition-specific and organism-specific behavior.