Paper Info
Title
Reconstruction of genetic association networks from microarray data: a partial least squares approach.
Abstract
Motivation: Gene association/interaction networks provide vast amounts of information about essential processes inside the cell. A complete picture of genegene associations/interactions would open new horizons for biologists, ranging from pure appreciation to successful manipulation of biological pathways for therapeutic purposes. Therefore, identification of important biological complexes whose members (genes and their products proteins) interact with each other is of prime importance. Numerous experimental methods exist but, for the most part, they are costly and labor intensive. Computational techniques, such as the one proposed in this work, provide a quick budget solution that can be used as a screening tool before more expensive techniques are attempted. Here, we introduce a novel computational method based on the partial least squares (PLS) regression technique for reconstruction of genetic networks from microarray data. Results: The proposed PLS method is shown to be an effective screening procedure for the detection of genegene interactions from microarray data. Both simulated and real microarray experiments show that the PLS-based approach is superior to its competitors both in terms of performance and applicability.
Year
DOI
Venue
2008
10.1093/bioinformatics/btm640
BIOINFORMATICS
Keywords
Field
DocType
genetic association,microarray data,interaction network
Prime (order theory),Data mining,Regression,Computer science,Partial least squares regression,Microarray analysis techniques,Software,Genetic association,Bioinformatics,Gene regulatory network
Journal
Volume
Issue
ISSN
24
4
1367-4803
Citations 
PageRank 
References 
13
1.29
9
Authors
3
Name
Order
Citations
PageRank
Vasyl Pihur1803.59
Somnath Datta239330.33
Susmita Datta337823.64