Post-processing strategies for improving local gene expression pattern analysis

Authors:
Qiang Wang;Yunming Ye;Joshua Zhexue Huang;Shengzhong Feng
Affiliations:
Department of Computer Science, Harbin Institute of Technology Shenzhen Graduate School, Xili, Shenzhen 518055, China;Department of Computer Science, Harbin Institute of Technology Shenzhen Graduate School, Xili, Shenzhen 518055, China;Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Xili, Shenzhen 518055, China;Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Xili, Shenzhen 518055, China
Venue:
International Journal of Data Mining and Bioinformatics
Year:
2013

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Abstract

This paper proposes a new analytical process highlighted by a soft subspace clustering method, a changing window technique, and a series of post-processing strategies to enhance the identification and characterisation of local gene expression patterns. The proposed method can be conducted in an interactive way, facilitating the exploration and analysis of local gene expression patterns in real applications. Experimental results have shown that the proposed method is effective in identification and characterization of functional gene groups in terms of both local expression similarities and biological coherence of genes in a cluster.