hou-effectivenonparametric-2007.pdf (416.73 kB)
An effective non-parametric method for globally clustering genes from expression profiles
journal contribution
posted on 2007-12-01, 00:00 authored by Jingyu HouJingyu Hou, W Shi, Gang LiGang Li, Wanlei ZhouClustering 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.
History
Journal
Medical and biological engineering and computingVolume
45Issue
12Pagination
1175 - 1185Publisher
SpringerLocation
Berlin, GermanyPublisher DOI
ISSN
0140-0118eISSN
1741-0444Language
engNotes
Published online: 18 October 2007. The original publication can be found at www.springerlink.comPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2007, International Federation for Medical and Biological EngineeringUsage metrics
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