Epistasis Blog

From the Artificial Intelligence Innovation Lab at Cedars-Sinai Medical Center (www.epistasis.org)

Sunday, March 19, 2006

New Grant on the Genome-Wide Analysis of Epistasis

The Dartmouth Computational Genetics Laboratory (CGL) is pleased to announce our NIH R01 on "Machine Learning Prediction of Cancer Susceptibility" (PI - Moore) will be funded by the National Library of Medicine (NLM) starting July 1st. This is a four-year grant that will focus on developing, evaluating, and applying novel computational methods for detecting, characterizing, and interpreting epistasis on a genome-wide scale in a large epidemiologic study of bladder cancer susceptibility. All methods and algorithms developed as part of this proposal will be released as part of our open-source MDR software package. The previous Epistasis Blog post on Genetic Programming is an example of the type of methodology we will be exploring.


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