Jason Moore is the Third Century Professor of Genetics and Director of the Institute for Quantitative Biomedical Sciences at the Geisel School of Medicine at Dartmouth College. He was previously an Ingram Associate Professor of Cancer Research at Vanderbilt University Medical School, where he held positions as Assistant and Associate Professor of Molecular Physiology and Biophysics. He has won numerous awards including the James V. Neel Young Investigator award from the International Genetic Epidemiology Society and a Best Paper award from the ACM Genetic and Evolutionary Computing Conference (GECCO). He is an elected Fellow of the American Association for the Advancement of Science and is a Kavli Fellow of the National Academy of Sciences. He is currently Editor in Chief of the open-access journal BioData Mining, which is published by BioMed Central.
Moore is a graduate of the University of Michigan in Ann Arbor, where he earned an MS in Human Genetics, an MA in Applied Statistics, and a PhD in Human Genetics. His dissertation work focused on computational and statistical methods for the genetic analysis of blood pressure change over a 24-hour period. He is also a graduate of Florida State University in Tallahassee, where he earned a BS in Biological Sciences.
His research focuses on the development, evaluation, and application of data mining and machine learning methods for the identification of genetic, genomic, and proteomic predictors of common human diseases, such as cancer and cardiovascular disease. Moore and his team have developed a number of novel machine learning methods, including multifactor dimensionality reduction (MDR) that uses constructive induction to detect nonlinear interactions among two or more attributes. He has published more than 350 peer-reviewed papers, editorials, and book chapters, and is funded by multiple grants from the National Institutes of Health. More information about Moore and his work can be found at epistasis.org and iQBS.org.