Analysis of protein-protein interaction network using Markov clustering with pigeon-inspired optimization algorithm in HIV (human immunodeficiency virus)

Alhadi B., M. S. Wisnubroto, Dian Lestari

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As a well-known clustering algorithm, Markov Clustering (MCL) has been used in many areas due to its simplicity and the ability to detect a cluster of different sizes and shapes for example clustering in bioinformatics. MCL shows good performance as a fast and scalable unsupervised cluster algorithm for graphs. However, a limitation of MCL is that the clustering results are mostly dependent on its inflation parameter whose value is user specified. In this paper, we develop a new method named as PIO-MCL to detected protein-protein interaction network by using Pigeon-Inspired Optimization (PIO) Algorithm to optimize the parameter of inflating operator in MCL algorithm. The experiments on PPI dataset show that PIO-MCL outperforms the state of the art method for clustering protein-protein interaction in terms of several criteria.

Original languageEnglish
Title of host publicationProceedings of the 3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017
EditorsRatna Yuniati, Terry Mart, Ivandini T. Anggraningrum, Djoko Triyono, Kiki A. Sugeng
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735417410
DOIs
Publication statusPublished - 22 Oct 2018
Event3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017 - Bali, Indonesia
Duration: 26 Jul 201727 Jul 2017

Publication series

NameAIP Conference Proceedings
Volume2023
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017
CountryIndonesia
CityBali
Period26/07/1727/07/17

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  • Cite this

    B., A., Wisnubroto, M. S., & Lestari, D. (2018). Analysis of protein-protein interaction network using Markov clustering with pigeon-inspired optimization algorithm in HIV (human immunodeficiency virus). In R. Yuniati, T. Mart, I. T. Anggraningrum, D. Triyono, & K. A. Sugeng (Eds.), Proceedings of the 3rd International Symposium on Current Progress in Mathematics and Sciences 2017, ISCPMS 2017 [020229] (AIP Conference Proceedings; Vol. 2023). American Institute of Physics Inc.. https://doi.org/10.1063/1.5064226