Saurabh Sinha’s research falls into the area of computational regulatory genomics and big data genomics. His lab group is currently working on quantitative modeling of regulatory sequences (NIGMS R01 grant, 2015-18), with the goal of predicting gene expression levels from DNA sequence. The long-term vision for such modeling is to be able to predict how small changes in regulatory (non-gene) DNA may lead to changes in gene expression and phenotype.
Sinha’s group has discovered major components of the underlying transcriptional regulatory networks (TRNs), and collaborated with Mayo Clinic to discover TRNs underlying cancer drug sensitivity and its inter-individual variation (cancer pharmacogenomics). The genes and transcription factors that we predicted using our multi-omics analysis tools were confirmed experimentally in cancer models.
Sinha completed his PhD at the University of Washington, Seattle, joining the University of Illinois as a Professor of Computer Science in 2005. He serves as the co-Director and Research PI of the KnowEnG Center, where new cutting-edge tools are being developed to address major problems in cancer informatics. Sinha’s work brings a variety of computational and statistical approaches to bear upon these problems, including machine learning techniques for high dimensional genomics data, and incorporation of heterogeneous biological networks into machine learning tasks. Sinha is affiliated with the Carl R. Woese Institute of Genomic Biology, the Carle Illinois College of Medicine, the Biophysics Program, and the Department of Entomology.