標題: An evolutionary approach for gene expression patterns
作者: Tsai, HK
Yang, JM
Tsai, YF
Kao, CY
生物資訊及系統生物研究所
Institude of Bioinformatics and Systems Biology
關鍵字: clustering;genetic algorithm (GA);gene clustering;gene expression;gene ordering;heterogeneous pairing selection (HpS);microarray
公開日期: 1-Jun-2004
摘要: This study presents an evolutionary algorithm, called a heterogeneous selection genetic algorithm (HeSGA), for analyzing the patterns of gene expression on microarray data. Microarray technologies have provided the means to monitor the expression levels of a large number of genes simultaneously. Gene clustering and gene ordering are important in analyzing a large body of microarray expression data. The proposed method simultaneously solves gene clustering and gene-ordering problems by integrating global and local search mechanisms. Clustering and ordering information is used to identify functionally related genes and to infer genetic networks from immense microarray expression data. HeSGA was tested on eight test microarray datasets, ranging in size from 147 to 6221 genes. The experimental clustering and visual results indicate that HeSGA not only ordered genes smoothly but also grouped genes with similar gene expressions. Visualized results and a new scoring function that references predefined functional categories were employed to confirm the biological interpretations of results yielded using HeSGA and other methods. These results indicate that HeSGA has potential in analyzing gene expression patterns.
URI: http://dx.doi.org/10.1109/TITB.2004.826713
http://hdl.handle.net/11536/26689
ISSN: 1089-7771
DOI: 10.1109/TITB.2004.826713
期刊: IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE
Volume: 8
Issue: 2
起始頁: 69
結束頁: 78
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