A parallel genetic algorithm for single class pattern classification and its application for gene expression profiling in Streptomyces coelicolor.

ABSTRACT:

Background

Identification of coordinately regulated genes according to the level of their expression during the time course of a process allows for discovering functional relationships among genes involved in the process.

Results

We present a single class classification method for the identification of genes of similar function from a gene expression time series. It is based on a parallel genetic algorithm which is a supervised computer learning method exploiting prior knowledge of gene function to identify unknown genes of similar function from expression data. The algorithm was tested with a set of randomly generated patterns; the results were compared with seven other classification algorithms including support vector machines. The algorithm avoids several problems associ

SUBMITTER: To CC 

PROVIDER: S-EPMC1804277 | biostudies-literature | 2007 Feb

REPOSITORIES: biostudies-literature