Hypergraph based geometric biclustering algorithm

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

9 Scopus Citations
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Detail(s)

Original languageEnglish
Pages (from-to)1656-1665
Journal / PublicationPattern Recognition Letters
Volume33
Issue number12
Publication statusPublished - 1 Sept 2012

Abstract

In this paper, we present a hypergraph based geometric biclustering (HGBC) algorithm. In a high dimensional space, bicluster patterns to be recognized can be considered to be linear geometrical structures. We can use the Hough transform (HT) to find sub-biclusters which correspond to the linear structures in column-pair spaces. Then a hypergraph model is built to merge the sub-biclusters into larger ones. Experiments on simulated and real biological data show that the HGBC algorithm proposed here can combine the sub-biclusters efficiently and provide more accurate classification results compared with existing biclustering methods. © 2012 Elsevier B.V. All rights reserved.

Research Area(s)

  • Biclustering, DNA microarray data analysis, Hough transform, Hypergraph partition

Citation Format(s)

Hypergraph based geometric biclustering algorithm. / Wang, Zhiguan; Yu, Chi Wai; Cheung, Ray C.C. et al.
In: Pattern Recognition Letters, Vol. 33, No. 12, 01.09.2012, p. 1656-1665.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review