An effective non-parametric method for globally clustering genes from expression profiles
Hou, Jingyu, Shi, Wei, Li, Gang and Zhou, Wanlei 2007, An effective non-parametric method for globally clustering genes from expression profiles, Medical and biological engineering and computing, vol. 45, no. 12, pp. 1175-1185.
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Clustering is widely used in bioinformatics to find gene correlation patterns. Although many algorithms have been proposed, these are usually confronted with difficulties in meeting the requirements of both automation and high quality. In this paper, we propose a novel algorithm for clustering genes from their expression profiles. The unique features of the proposed algorithm are twofold: it takes into consideration global, rather than local, gene correlation information in clustering processes; and it incorporates clustering quality measurement into the clustering processes to implement non-parametric, automatic and global optimal gene clustering. The evaluation on simulated and real gene data sets demonstrates the effectiveness of the algorithm.
Published online: 18 October 2007. The original publication can be found at www.springerlink.com
Field of Research
080301 Bioinformatics Software 080109 Pattern Recognition and Data Mining
Socio Economic Objective
970106 Expanding Knowledge in the Biological Sciences
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