Sushmita Roy’s 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.
Roy is interested in identifying networks under different environmental, developmental and evolutionary contexts, comparing these networks across contexts, and constructing predictive models from these networks.
Specifically, some research topics of interest are:
Inference of structure and function of regulatory networks
Comparative analysis of expression modules across species
Evolution of gene regulation
Relational learning to predict function
Modeling condition-specific functional behavior
Learning causal networks
Predictive models of phenotypic response