Greg Carter
Computational Biology and Genetics Current Position
Senior Research Scientist Degree
PhD, Physics, University of Minnesota, 1997 Research Interests
Dr. Carter's primary field of research is the computational genetics of complex phenotypes, with the aim of understanding how multiple genes combine to affect outcomes in biological systems. This work involves the development of novel numerical methods for analysis and modeling of cell behavior under multiple environmental and genetic perturbations. Information on cellular function from gene expression and other high-throughput phenotype assays can be integrated with molecular interaction data to formulate models that systematically predict the results of novel stimuli or perturbations. These models are designed to enable the formulation of genetically complex hypotheses that can be directly tested in the laboratory. The long-term goal of this research is to develop models for understanding the multigenic, molecular basis of human diseases, allowing the identification of candidate genes for targeted therapeutic intervention and, ultimately, the personalization of prognosis and therapies. Selected Publications
Carter GW, Galas DJ, and Galitski T. Maximal Extraction of Biological Information from Genetic Interaction Data. 2009. PLoS Computational Biology 5(4):e1000347. Carter GW, Prinz S, Neou C, Shelby JP, Marzolf B, Thorsson V, and Galitski T. Prediction of phenotype and genomic expression for combinations of mutations. 2007. Molecular Systems Biology 3:96. Carter GW, Rupp S, Fink GR, and Galitski T. Disentangling information flow in the Ras-cAMP signaling network. 2006. Genome Research 16: 520-526. Drees BL, Thorsson V, Carter GW, Rives AW, Raymond M, Avila-Campillo I, Shannon P, and Galitski T. Derivation of genetic interaction networks from quantitative phenotype data. 2005. Genome Biology 6: R38.