We are a computational biology group interested in developing statistical machine learning methods to understand gene regulatory networks driving cellular functions. We are interested in identifying networks under different environmental, developmental, disease and evolutionary contexts and examining their dynamics. We ultimately aim to construct predictive models from these molecular networks that can inform us how the system will behave under different perturbations. We develop tools for bulk and single cell omic datasets and apply them to diverse biological and biomedical questions with the central theme of understanding gene regulation. Learn more about our research.
The Latest at Roy Lab
Computational Tools Unlock Evolutionary Complexity
With a new computational approach led by Roy lab member Junha Shin, publicly-available gene expression datasets, and the new data, Roy and her collaborators were able to connect changes in protein levels to phenotypic traits.
New tool predicts three-dimensional organization of human chromosomes
Sushmita Roy and Shilu Zhang have developed a computational tool that can accurately predict the three-dimensional interactions between regions of human chromosomes.
UW–Madison research team finds new ways to generate stem cells more efficiently
Combined laboratory and computational methods lead to better completion of pluripotency, a faster process, and improved understanding of how cells become reprogrammed from one cell type to another.
Data Science Initiative supports faculty research
Network-based Analysis of Cellular Heterogeneity will receive University of Wisconsin–Madison Data Science Initiative funding
Siahpirani paper earns top 10 at RECOMB/ISCB 2017
Congratulations to Alireza Siahpirani! His paper A prior-based integrative framework for functional transcriptional regulatory network inference earned a top 10 rating at RECOMB/ISCB November 19-21, 2017 in New York City, NY. ISCB is the leading professional society for computational biology and bioinformatics. Check out Siahpirani's paper and the other top rated papers.