Clustering of Microarray data via Clique Partitioning期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

Clustering of Microarray data via Clique Partitioning

Authors:	Gary?Kochenberger author-information" > author-information__contact u-icon-before" > mailto:Gary.Kochenberger@Cudenver.edu" title=" Gary.Kochenberger@Cudenver.edu" itemprop=" email" data-track=" click" data-track-action=" Email author" data-track-label=" " >Email author,Fred?Glover,Bahram?Alidaee,Haibo?Wang

Affiliation:	(1) School of Business, University of Colorado at Denver, Denver;(2) Leeds School of Business, University of Colorado at Boulder, Boulder;(3) School of Business, University of Mississippi, Mississippi;(4) School of Business, Texas A&M International University, Texas

Abstract:	Microarrays are repositories of gene expression data that hold tremendous potential for new understanding, leading to advances in functional genomics and molecular biology. Cluster analysis (CA) is an early step in the exploration of such data that is useful for purposes of data reduction, exposing hidden patterns, and the generation of hypotheses regarding the relationship between genes and phenotypes. In this paper we present a new model for the clique partitioning problem and illustrate how it can be used to perform cluster analysis in this setting.

Keywords:	clustering clique partitioning metaheuristics
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