Three Research Areas:

(1) Biomedical Informatics in Personalized Medicine. Medicine in the future depends on seamless integration of information from diverse sources: genomics, high-throughput assay, clinical trials, and drugs. There is a great need to unleash the fount of data from heterogenous origins into actionable therapies. We have developed a web service to integrate information from clinical trials and drugs for targeted cancer therapies. The web service is named IDICAP, which is available from here.

(2) Transcriptome study using Next Generation Sequencing (NGS). NGS is a powerful DNA sequencing technology that has helped to profile gene expression patterns, elucidate genomic variations, sequence genomes of different organisms, and many more. My lab focuses on the computational aspects of applying NGS for transcriptome study of Lyme infection, Immunity, and visual system in red-eared slider turtle.

(3) Applications of machine learning in comparative genomics. We developed a supervised machine learning technique – logistic regression – to build a classifier to recognize polyadenylation site in mammals, chicken, Drosophila, and plants. We have expanded this approach to study codon usage and translation initiation sites.