INTERESTS
Bioinformatics; Cancer Genomics; Isoform-level Gene Regulation; Epigenetics; Alternative Promoters and Alternative Splicing.
RESEARCH
Hypothesis: The central hypothesis of his laboratory research is that the isoform-level gene products “transcript variants” and “protein isoforms” are the basic functional units in the mammalian cell, and accordingly, the informatics platforms – ranging from basic molecular biology data management systems to the biomarker and therapeutic drug target discovery for precision medicine – should adapt “gene isoform centric” rather than “gene centric” approaches.
Dr Davuluri is a leader in bioinformatics and data science research. He has more than 20 years of progressive working experience in the areas of bioinformatics and computational genomics; a strong background in statistics and computer science; and synergistic expertise in statistical pattern recognition, machine learning, genomics and bioinformatics. He has served as PI of several multi-investigator and multi-site projects. His lab currently focuses on developing machine learning algorithms and informatics solutions for problems in isoform-level gene regulation and precision-medicine. The overarching goal of the lab is to translate data from high dimensional (-omic) platforms (e.g., NextGen sequencing) to derive experimentally interpretable and testable discovery models towards genomics-based decision support systems. His group is developing bioassays that can rapidly identify biomarkers from human tissue and blood samples. Towards these goals, his group applies a combination of state-of-the-art statistically rigorous data-mining methods and high-throughput experimental procedures in a systems biology setting.