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Verfasst von:Maulik, Ujjwal [VerfasserIn]   i
 Mukhopadhyay, Anirban [VerfasserIn]   i
 Bhattacharyya, Malay [VerfasserIn]   i
 Kaderali, Lars [VerfasserIn]   i
 Brors, Benedikt [VerfasserIn]   i
 Bandyopadhyay, Sanghamitra [VerfasserIn]   i
 Eils, Roland [VerfasserIn]   i
Titel:Mining quasi-bicliques from HIV-1-human protein interaction network
Titelzusatz:a multiobjective biclustering approach
Verf.angabe:Ujjwal Maulik, Anirban Mukhopadhyay, Malay Bhattacharyya, Lars Kaderali, Benedikt Brors, Sanghamitra Bandyopadhyay, and Roland Eils
Jahr:2013
Umfang:13 S.
Teil:volume:10
 year:2013
 number:2
 month:03/04
 pages:423-435
 extent:13
Fussnoten:Published online 28 Nov. 2012 ; Gesehen am 29.06.2021
Titel Quelle:Enthalten in: Institute of Electrical and Electronics EngineersIEEE ACM transactions on computational biology and bioinformatics
Ort Quelle:New York, NY : IEEE, 2004
Jahr Quelle:2013
Band/Heft Quelle:10(2013), 2 vom: März/Apr., Seite 423-435
ISSN Quelle:1557-9964
Abstract: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.
DOI:doi:10.1109/TCBB.2012.139
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext: https://doi.org/10.1109/TCBB.2012.139
 DOI: https://doi.org/10.1109/TCBB.2012.139
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:biclustering
 Bioinformatics
 Biological cells
 Bipartite graph
 HIV-1
 Humans
 Linear programming
 multiobjective optimization
 Optimization
 Protein-protein interaction
 Proteins
 quasi-biclique
K10plus-PPN:1761486799
Verknüpfungen:→ Zeitschrift

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