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Senior Research Scientists
John Boyle
Greg Carter
Eric Deutsch
Alan Diercks
Gustavo Glusman
Mark Gilchrist
Liz Gold
Nat Goodman
Marta Janer
Christopher Lausted
Simon Letarte
Monica Orellana
Jacques Peschon
Shizhen Qin
Stephen Ramsey
David Reiss
Lee Rowen
Alistair Rust
Arian Smit
Jennifer Smith
James Spotts
Vesteinn Thorsson
Qiang Tian
Julian Watts
 Greg Carter
Greg Carter

Susan Lindquest

Greg Carter

Area of Expertise
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, 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.




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