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A GRASP metaheuristic for microarray data analysis
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DOI：10.1016/j.cor.2012.10.008.png)
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Abstract
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The Weighted Gene Regulatory Network (WGRN) problem consists in pruning a regulatory network obtained from DNA microarray gene expression data, in order to identify a reduced set of candidate elements which can explain the expression of all other genes. Since the problem appears to be particularly hard for general-purpose solvers, we develop a Greedy Randomized Adaptive Search Procedure (GRASP) and refine it with three alternative Path Relinking procedures. For comparison purposes, we also develop a Tabu Search algorithm with a self-adapting tabu tenure. The experimental results show that GRASP performs better than Tabu Search and that Path Relinking significantly contributes to its effectiveness. (C) 2012 Elsevier Ltd. All rights reserved.
Keywords:
Gene regulatory networks
DNA microarray data
GRASP
Path Relinking
Tabu Search
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