Biclustering protein interactions between HIV-1 proteins and humans proteins using LCM-MBC algorithm

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Some of the protein interactions are still unidentified. Thus, many research about protein interactions had been held. HIV-1 is a dangerous virus that has no medicine yet. The research about HIV-1 proteins and human proteins interactions leads to the insight of drug target prediction. Biclustering technique is the beginning step before the prediction step. Biclustering is the process to cluster the dataset through two perspectives. The result of biclustering can be applied to predict unidentified protein interactions. Currently, this technique is more efficiently and effectively than the experimental method. The LCM-MBC is one of the biclustering algorithms to find biclusters from protein interactions dataset. This algorithm uses graph theory as the basic to obtain the maximal biclique. The algorithm can represent as enumeration tree. Every subtree result from the bicliques which are the biclusters. This algorithm performs quickly and efficiently in the term of memory consumptions. In this research, we apply the LCM-MBC algorithm for 16215 types of interactions between HIV-1 proteins and human proteins. We find 852 biclusters which the maximal bicluster has a size of 4 rows and 204 columns.

Original languageEnglish
Title of host publicationProceedings of the Symposium on BioMathematics, SYMOMATH 2018
EditorsBevina Desjwiandra Handari, Hiromi Seno, Hengki Tasman
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735418141
Publication statusPublished - 22 Mar 2019
EventInternational Symposium on BioMathematics 2018, SYMOMATH 2018 - Depok, Indonesia
Duration: 31 Aug 20182 Sep 2018

Publication series

NameAIP Conference Proceedings
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616


ConferenceInternational Symposium on BioMathematics 2018, SYMOMATH 2018


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