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Identifying pathways of coordinated gene expression.
MedLine Citation:
PMID:  23192542     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
Methods capable of identifying genetic pathways with coordinated expression signatures are critical to advance our understanding of the functions of biological networks. Currently, the most comprehensive and validated biological networks are metabolic networks. Complete metabolic networks are easily sourced from multiple online databases. These databases reveal metabolic networks to be large, highly complex structures. This complexity is sufficient to hide the specific details on which pathways are interacting to produce an observed network response. In this chapter we will outline a complete framework for identifying the metabolic pathways that relate to an observed phenomenon. To illuminate the functional metabolic pathways, we overlay microarray experiments on top of a complete metabolic network. We then extract the functional components within a metabolic network through a combination of novel pathway ranking, clustering, and classification algorithms. This chapter is designed as a simple tutorial which enables this framework to be applied to any metabolic network and microarray data.
Authors:
Timothy Hancock; Ichigaku Takigawa; Hiroshi Mamitsuka
Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Methods in molecular biology (Clifton, N.J.)     Volume:  939     ISSN:  1940-6029     ISO Abbreviation:  Methods Mol. Biol.     Publication Date:  2013  
Date Detail:
Created Date:  2012-11-29     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9214969     Medline TA:  Methods Mol Biol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  69-85     Citation Subset:  IM    
Affiliation:
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Japan, timhancock@kuicr.kyoto-u.ac.jp.
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