To understand how the human genome and its numerous genetic polymorphisms interpret the lifestyle of the individual – diet and physical activity among others – in ways that affect risk of cardiovascular disease, type 2 diabetes, hypertension and obesity. This is done with computational tools and databases, with a goal of describing factors pertinent to personalized nutrition.
- PhD, Cellular and Molecular Biology, University of Wisconsin, Madison
Dr. Larry Parnell is a USDA-ARS Computational Biologist on the Nutrition and Genomics Team at the HNRCA. His research focuses on the use of computational methods to discern signals from genomics and metabolomics data that identify genes, metabolites and pathways involved dietary response, obesity, type 2 diabetes, heart diseases, and age-related diseases. In his most recent research, Dr. Parnell employs systems biology approaches, machine learning and network analysis to gain further insight into how the genome interprets dietary intakes and exercise in the context of aging and age-related diseases. Since joining ARS in 2003, Dr. Parnell has co-authored over 110 peer-reviewed research articles. Prior to that, he co-authored publications on the first reports of sequencing the human genome and the first plant genome (Arabidopsis thaliana). Dr. Parnell is an adjunct assistant professor at the Friedman School of Nutrition Science and Policy and has served as a reviewer of research grant applications for NIH T32 training grants in heart disease research, the Plant Genome Initiative (National Science Foundation,) and for the European Community. He has received over 20 separate invitations to speak on the research of the Nutrition and Genomics Team during his tenure with the ARS. Dr. Parnell is a member of the American Society of Human Genetics and the African Society for Bioinformatics and Computational Biology.
For more information on Dr. Laurence Parnell, please visit the USDA, Agricultural Research Service website (Clicking this link takes you off the Tufts University website and to a federal website).