Support Vector Methods for Functional Genomic Analysis. Start date: April 2004. Expires: March 2007. Amount: $158,517. Principal investigator: William Noble. Sponsor: University of Washington.
Project will develop machine-learning techniques that will classify genes into discrete functional categories in order to infer gene function from genomic data. The grantee will build on prior work, which showed that a support vector machine can be successfully trained using DNA microarray expression data to recognize various gene functional categories.