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Mining Quasi-Bicliques from HIV-1-Human Protein Interaction Network: A Multiobjective Biclustering Approach
March-April 2013 (vol. 10 no. 2)
pp. 423-435
Ujjwal Maulik, Jadavpur University, Kolkata
Anirban Mukhopadhyay, University of Kalyani, Kalyani
Malay Bhattacharyya, University of Kalyani, Kalyani
Lars Kaderali, Dresden University of Technology, Dresden
Benedikt Brors, University of Heideberg, Heideberg
Sanghamitra Bandyopadhyay, Indian Statistical Institute, Kolkata
Roland Eils, University of Heideberg, Heideberg
In this work, we model the problem of mining quasi-bicliques from weighted viral-host protein-protein interaction network as a biclustering problem for identifying strong interaction modules. In this regard, a multiobjective genetic algorithm-based biclustering technique is proposed that simultaneously optimizes three objective functions to obtain dense biclusters having high mean interaction strengths. The performance of the proposed technique has been compared with that of other existing biclustering methods on an artificial data. Subsequently, the proposed biclustering method is applied on the records of biologically validated and predicted interactions between a set of HIV-1 proteins and a set of human proteins to identify strong interaction modules. For this, the entire interaction information is realized as a bipartite graph. We have further investigated the biological significance of the obtained biclusters. The human proteins involved in the strong interaction module have been found to share common biological properties and they are identified as the gateways of viral infection leading to various diseases. These human proteins can be potential drug targets for developing anti-HIV drugs.
Index Terms:
Proteins,Humans,Bipartite graph,Biological cells,Optimization,Linear programming,Bioinformatics,quasi-biclique,Proteins,Humans,Bipartite graph,Biological cells,Optimization,Linear programming,Bioinformatics,multiobjective optimization,Protein-protein interaction,HIV-1,biclustering
Citation:
Ujjwal Maulik, Anirban Mukhopadhyay, Malay Bhattacharyya, Lars Kaderali, Benedikt Brors, Sanghamitra Bandyopadhyay, Roland Eils, "Mining Quasi-Bicliques from HIV-1-Human Protein Interaction Network: A Multiobjective Biclustering Approach," IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 10, no. 2, pp. 423-435, March-April 2013, doi:10.1109/TCBB.2012.139
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