The role of indirect connections in gene networks in predicting function

Gillis, J., Pavlidis, P. (2011) The role of indirect connections in gene networks in predicting function. Bioinformatics, 27 (13). pp. 1860-1866. ISSN 13674803 (ISSN)

URL: http://www.ncbi.nlm.nih.gov/pubmed/21551147
DOI: 10.1093/bioinformatics/btr288

Abstract

Motivation: Gene networks have been used widely in gene function prediction algorithms, many based on complex extensions of the 'guilt by association' principle. We sought to provide a unified explanation for the performance of gene function prediction algorithms in exploiting network structure and thereby simplify future analysis. Results: We use co-expression networks to show that most exploited network structure simply reconstructs the original correlation matrices from which the co-expression network was obtained. We show the same principle works in predicting gene function in protein interaction networks and that these methods perform comparably to much more sophisticated gene function prediction algorithms. © The Author 2011. Published by Oxford University Press. All rights reserved.

Item Type: Paper
Uncontrolled Keywords: protein algorithm animal article gene expression gene regulatory network genetics human mouse yeast Algorithms Animals Gene Regulatory Networks Humans Mice Proteins Yeasts
Subjects: bioinformatics > genomics and proteomics > computers
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics
bioinformatics > genomics and proteomics > computers > computer software
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > genes, structure and function
CSHL Authors:
Communities: CSHL labs > Gillis Lab
Depositing User: Matt Covey
Date Deposited: 04 Apr 2013 13:54
Last Modified: 29 Apr 2013 19:04
PMCID: PMC3117376
Related URLs:
URI: http://repository.cshl.edu/id/eprint/28085

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