title: Post-processing strategies for improving local gene expression pattern analysis.
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.
authors: Department of Computer Science, Harbin Institute of Technology Shenzhen Graduate School, Xili, Shenzhen 518055, China. mikewq@yahoo.cn
authors: Qiang
authors: Q
authors: Wang
authors: Yunming
authors: Y
authors: Ye
authors: Joshua Zhexue
authors: JZ
authors: Huang
authors: Shengzhong
authors: S
authors: Feng
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D015870:Gene Expression; D020869:Gene Expression Profiling / Q000379:methods*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods