Analysis and prediction of protein interactions between HIV-1 protein and human protein using LCM-MBC algorithm combined with association rule mining

Titin Siswantining, Alhadi Bustamam, Olivia Swasti, Herley Shaori Al-Ash

Abstract


Human Immunodeficiency Virus (HIV) is a virus that attacks the human immune system. This virus consists of 23 proteins in a single-stranded RNA. The protein interaction between HIV proteins and human proteins can impact to AIDS. The research about HIV-1 proteins and human proteins interactions leads to the insight of drug-target prediction. To analyze protein interactions carried out by the biclustering process. We divide the proteins interactions became a directed graph. The LCM-MBC algorithm is a biclustering algorithm used to analyze protein interactions—this algorithm based on directed graph theory. The results of biclustering used to predict with association rule mining. There is 45 bicluster that has five HIV proteins in one bicluster. From the bicluster obtained, 11 HIV-1 proteins are predicted to interact with 36 human proteins. If human protein interacts with HIV-1 proteins, it means that human proteins will relate according to the interaction type by HIV proteins.

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Published: 2021-07-20

How to Cite this Article:

Titin Siswantining, Alhadi Bustamam, Olivia Swasti, Herley Shaori Al-Ash, Analysis and prediction of protein interactions between HIV-1 protein and human protein using LCM-MBC algorithm combined with association rule mining, Commun. Math. Biol. Neurosci., 2021 (2021), Article ID 64

Copyright © 2021 Titin Siswantining, Alhadi Bustamam, Olivia Swasti, Herley Shaori Al-Ash. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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