@inproceedings{f2651a142e4f4dcc9cf39cbc172a1103,
title = "Biclustering protein interactions between HIV-1 proteins and humans proteins using LCM-MBC algorithm",
abstract = "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.",
author = "Olivia Swasti and Alhadi Bustamam and Dian Lestari and Wibowo Mangunwardoyo",
note = "Publisher Copyright: {\textcopyright} 2019 Author(s).; International Symposium on BioMathematics 2018, SYMOMATH 2018 ; Conference date: 31-08-2018 Through 02-09-2018",
year = "2019",
month = mar,
day = "22",
doi = "10.1063/1.5094279",
language = "English",
series = "AIP Conference Proceedings",
publisher = "American Institute of Physics Inc.",
editor = "Handari, {Bevina Desjwiandra} and Hiromi Seno and Hengki Tasman",
booktitle = "Proceedings of the Symposium on BioMathematics, SYMOMATH 2018",
address = "United States",
}
