A statistical method to incorporate biological knowledge for generating testable novel gene regulatory interactions from microarray experiments.

ABSTRACT:

Background

The incorporation of prior biological knowledge in the analysis of microarray data has become important in the reconstruction of transcription regulatory networks in a cell. Most of the current research has been focused on the integration of multiple sets of microarray data as well as curated databases for a genome scale reconstruction. However, individual researchers are more interested in the extraction of most useful information from the data of their hypothesis-driven microarray experiments. How to compile the prior biological knowledge from literature to facilitate new hypothesis generation from a microarray experiment is the focus of this work. We propose a novel method based on the statistical analysis of reported gene interactions in PubMed literature.

Results

SUBMITTER: Larsen P 

PROVIDER: S-EPMC2082045 | biostudies-literature | 2007 Aug

REPOSITORIES: biostudies-literature