The biclique k-clustering problem in bipartite graphs and its application in bioinformatics

V. Acuña; C. E. Ferreira; A. S. Freire; E. Moreno

doi:10.1016/j.endm.2010.05.021

The biclique k-clustering problem in bipartite graphs and its application in bioinformatics

V. Acuña, C. E. Ferreira, A. S. Freire, E. Moreno

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

In this paper we study the biclique k-clustering problem (B. kCP) in bipartite graphs, a generalization of the maximum edge biclique problem which has several applications in biological data analysis. We present an application of the B. kCP in bioinformatics, and introduce two integer linear formulations for the problem. Finally, we discuss the approximability of the problem and show computational experiments with random generated instances and also with instances that come the application.

Original language	English
Pages (from-to)	159-166
Number of pages	8
Journal	Electronic Notes in Discrete Mathematics
Volume	36
Issue number	C
DOIs	https://doi.org/10.1016/j.endm.2010.05.021
State	Published - Aug 2010
Externally published	Yes

Keywords

Biclique clustering
Biclustering
Maximum edge biclique

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10.1016/j.endm.2010.05.021

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abstract = "In this paper we study the biclique k-clustering problem (B. kCP) in bipartite graphs, a generalization of the maximum edge biclique problem which has several applications in biological data analysis. We present an application of the B. kCP in bioinformatics, and introduce two integer linear formulations for the problem. Finally, we discuss the approximability of the problem and show computational experiments with random generated instances and also with instances that come the application.",

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AU - Freire, A. S.

AU - Moreno, E.

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AB - In this paper we study the biclique k-clustering problem (B. kCP) in bipartite graphs, a generalization of the maximum edge biclique problem which has several applications in biological data analysis. We present an application of the B. kCP in bioinformatics, and introduce two integer linear formulations for the problem. Finally, we discuss the approximability of the problem and show computational experiments with random generated instances and also with instances that come the application.

KW - Biclique clustering

KW - Biclustering

KW - Maximum edge biclique

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The biclique k-clustering problem in bipartite graphs and its application in bioinformatics

Abstract

Keywords

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