Kyoto Encyclopedia of Genes and Genomes (KEGG) includes a collection of manually drawn pathway maps representing our knowledge on the molecular interaction and reaction networks for metabolism, genetic information processing, environmental information processing, cellular processes, human diseases and drug development.
Published in Chapter:
Structural Learning of Genetic Regulatory Networks Based on Prior Biological Knowledge and Microarray Gene Expression Measurements
Yang Dai (University of Illinois at Chicago, USA), Eyad Almasri (University of Illinois at Chicago, USA), Peter Larsen (University of Illinois at Chicago, USA), and Guanrao Chen (University of Illinois at Chicago, USA)
Copyright: © 2010
|Pages: 21
DOI: 10.4018/978-1-60566-685-3.ch012
Abstract
The reconstruction of genetic regulatory networks from microarray gene expression measurements has been a challenging problem in bioinformatics. Various methods have been proposed for this problem including the Bayesian Network (BN) approach. In this chapter, we provide a comprehensive survey of the current development of using structure priors derived from high-throughput experimental results such as protein-protein interactions, transcription factor binding location data, evolutionary relationships, and literature database in learning regulatory networks.