Computational Biologist
Current• Developed an integrated effort using data from GWA studies, QTLs, expression arrays, population-specific markers, and animal models to identify novel markers and genes for obesity, metabolic syndrome and type 2 diabetes.• Initiated systems biology approaches utilizing disease networks and genetic variants to understand gene-environment interactions.• Candidate gene identification for nutrition projects: obesity, type 2 diabetes, CVD• Analysis and organization of genetic variation (SNP) data, including GWAS data and putative biological consequences of different SNP alleles.• Led a team in designing cheminformatics software to identify food compounds with potential pharmacological properties. Our PhyteByte software compares natural products to drugs via machine learning (random forest).• Built SQL-based human nutrigenomics and nutrigenetics databases.• Allele-specific regulation of gene expression pertaining to response to environment.• Analysis of microarray data from Drosophila longevity studies to identify longevity genes.• Built a database of diet- and drug-gene interactions with a cardiovascular disease focus.• Comparative genomics (human, mouse, Drosophila) of genes involved in longevity.• Manage projects involving database design, candidate gene identification and software development as well as overall strategic planning.• Engaged in Center activities to develop a 5-year strategic plan.• Coordinating development of a systems biology working group at Tufts.
