Building pathway clusters from Random Forests classification using class votes.

ABSTRACT:

Background

Recent years have seen the development of various pathway-based methods for the analysis of microarray gene expression data. These approaches have the potential to bring biological insights into microarray studies. A variety of methods have been proposed to construct networks using gene expression data. Because individual pathways do not act in isolation, it is important to understand how different pathways coordinate to perform cellular functions. However, there are no published methods describing how to build pathway clusters that are closely related to traits of interest.

Results

We propose to build pathway clusters from pathway-based classification methods. The proposed methods allow researchers to identify clusters of pathways sharing similar functions. These

SUBMITTER: Pang H 

PROVIDER: S-EPMC2335306 | biostudies-literature | 2008 Feb

REPOSITORIES: biostudies-literature