Jody Hey

Professor
Department of Biology
Temple University
United States of America

Biography

Jody Hey is an evolutionary biologist at Temple University. In the 1980s and 1990s he did research on natural selection and species divergence in fruit flies (Drosophila). More recently he has worked on the development of methods for studying evolutionary divergence, on the divergence of cichlid fishes from Lake Malawi, on chimpanzees and on human populations. His research on divergence and speciation also lead him to study the difficulties of identifying species.

Research Intrest

Research at the laboratory of Dr. Hey lab includes theoretical and computational approach to find basic questions about how the evolutionary process has shaped life on earth. Much of his research focuses on how populations and closely related species have diverged, and on developing tools (computer programs) for analyzing this divergence.He develop methods that can take advantage of population genomic data, including the use of linkage information, and the use of very large data sets for the study of especially recent demographic changes and instances of natural selection. Hey has also conducted mathematical and statistical research in population genetics. He is the author of several computer programs that are used by other biologists for questions in population genetics. In 2004 Hey and Rasmus Nielsen produced the computer program IM, which implements a method for fitting an isolation-with-migration model to a pair of closely related populations or species. They updated this method with a new program in 2007 called IMa.

List of Publications
Sethuraman A, Hey J (2016) IMa2p - parallel MCMC and inference of ancient demography under the Isolation with migration (IM) model. Molecular Ecology Resources 16: 206-215.
Knoblauch J, Sethuraman A, Hey J (2017) IMGui - a desktop GUI applicatoin for isolation with migration analyses. Molecular Biology and Evolution 34:500-504.
Chung Y, Hey J (2017) Bayesian Analysis of Evolutionary Divergence with Genomic Data under Diverse Demographic Models. Molecular Biology and Evolution 34:1517-1528.

Global Scientific Words in Bioinformatics and Systems Biology