NDLI: A novel biclustering with parallel genetic algorithm

Content Provider	IEEE Xplore Digital Library
Author	Wei Shen ChengJun Xie GuiXia Liu Chong Xing MingQian Wang You Zhou
Copyright Year	2011
Description	Author affiliation: College of Computer Science and Technology, Jilin University, Changchun, 130012, China (Wei Shen; GuiXia Liu; Chong Xing; You Zhou) \|\| College of Computer Science and Technology, Beihua University, Jilin, 132021, China (ChengJun Xie) \|\| Changchun Institute of Engineering Technology, Changchun, 130117, China (MingQian Wang)
Abstract	A novel biclustering algorithm is proposed in this paper, which can be used to cluster gene expression data. One of the contributions of this paper is a novel and effective residue function of the biclustering algorithm. Furthermore, the parallel genetic algorithm is firstly used to the algorithm of the biclustering for gene expression data. This method can avoid local convergence in the optimal algorithm mostly. The Yeast Saccharomyces cerevisiae cell cycle gene expression profiles from the Spellman's data to bicluster are used to test the performance of new algorithm. And we compared our algorithm with traditional genetic algorithm in biclustering. The results reveal that novel proposed algorithms could discover the interesting patterns in the gene expression profiles.
Starting Page	900
Ending Page	903
File Size	319412
Page Count	4
File Format	PDF
ISBN	9781612847238
e-ISBN	9781612847269
DOI	10.1109/HHBE.2011.6028968
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-19
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Biclustering Software algorithms Clustering algorithms Residue function Prediction algorithms Gene expression profiles Parallel genetic algorithm Gene expression Genetic algorithms
Content Type	Text
Resource Type	Article

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