A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network

Recent high-throughput experiments have generated protein-protein interaction data on a genomic scale, yielding the complete protein-protein interaction network for several organisms. Various graph clustering algorithms have been applied to protein interaction networks for detecting protein function...

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Main Authors:	Jamaludin, Sallim, Rozlina, Mohamed, Che, Yahaya, Roslina, Abdul Hamid
Format:	Article
Language:	English
Published:	American Scientific Publisher 2018
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/19955/ http://umpir.ump.edu.my/id/eprint/19955/ http://umpir.ump.edu.my/id/eprint/19955/ http://umpir.ump.edu.my/id/eprint/19955/1/A%20Hybrid%20ACO-Graph%20Entropy%20for%20Functional%20Modules.pdf

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spelling	ump-199552018-11-22T02:03:12Z http://umpir.ump.edu.my/id/eprint/19955/ A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network Jamaludin, Sallim Rozlina, Mohamed Che, Yahaya Roslina, Abdul Hamid QA75 Electronic computers. Computer science Recent high-throughput experiments have generated protein-protein interaction data on a genomic scale, yielding the complete protein-protein interaction network for several organisms. Various graph clustering algorithms have been applied to protein interaction networks for detecting protein functional modules. Although the previous algorithms are scalable and robust, their accuracy is still limited because of the complex connectivity found in protein interaction networks. The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. The adapted ACO (ACO-PFMDA) has obtained feasible solution but not as magnificent as those reported in the literature. Some shortcomings were identified and addressed by proposing a Modified Ant Colony Optimization Algorithm (ACO-PFMDM), which introduces two new scheme for controlling the two main parameters of ACO to solve PFMDP. Experiments on one popular benchmark dataset namely "Saccharomyces cerevisiae" which taken from two popular databases DIP and MIPS has been performed. The experimental result have proved that ACO-PFMDM have improved the overall performance of protein functional module detection. The search process of ACO-PFMDM has converged effectively compared to some state-of-art algorithms. Moreover, the proposed dynamic update of the heuristic parameters based on entropy has generated high quality tours and it can guide ants toward the effective solutions space in the initial search stages. American Scientific Publisher 2018-11 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/19955/1/A%20Hybrid%20ACO-Graph%20Entropy%20for%20Functional%20Modules.pdf Jamaludin, Sallim and Rozlina, Mohamed and Che, Yahaya and Roslina, Abdul Hamid (2018) A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network. Advanced Science Letters, 24 (10). pp. 7607-7610. ISSN 1936-6612 https://doi.org/10.1166/asl.2018.12987 doi: 10.1166/asl.2018.12987
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Jamaludin, Sallim Rozlina, Mohamed Che, Yahaya Roslina, Abdul Hamid A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network
description	Recent high-throughput experiments have generated protein-protein interaction data on a genomic scale, yielding the complete protein-protein interaction network for several organisms. Various graph clustering algorithms have been applied to protein interaction networks for detecting protein functional modules. Although the previous algorithms are scalable and robust, their accuracy is still limited because of the complex connectivity found in protein interaction networks. The Ant Colony Optimization (ACO) Algorithm has been adapted for the protein functional module detection by modeling the problem as an optimization problem. The adapted ACO (ACO-PFMDA) has obtained feasible solution but not as magnificent as those reported in the literature. Some shortcomings were identified and addressed by proposing a Modified Ant Colony Optimization Algorithm (ACO-PFMDM), which introduces two new scheme for controlling the two main parameters of ACO to solve PFMDP. Experiments on one popular benchmark dataset namely "Saccharomyces cerevisiae" which taken from two popular databases DIP and MIPS has been performed. The experimental result have proved that ACO-PFMDM have improved the overall performance of protein functional module detection. The search process of ACO-PFMDM has converged effectively compared to some state-of-art algorithms. Moreover, the proposed dynamic update of the heuristic parameters based on entropy has generated high quality tours and it can guide ants toward the effective solutions space in the initial search stages.
format	Article
author	Jamaludin, Sallim Rozlina, Mohamed Che, Yahaya Roslina, Abdul Hamid
author_facet	Jamaludin, Sallim Rozlina, Mohamed Che, Yahaya Roslina, Abdul Hamid
author_sort	Jamaludin, Sallim
title	A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network
title_short	A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network
title_full	A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network
title_fullStr	A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network
title_full_unstemmed	A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network
title_sort	hybrid aco-graph entropy for functional modules detection from protein-protein interaction network
publisher	American Scientific Publisher
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/19955/ http://umpir.ump.edu.my/id/eprint/19955/ http://umpir.ump.edu.my/id/eprint/19955/ http://umpir.ump.edu.my/id/eprint/19955/1/A%20Hybrid%20ACO-Graph%20Entropy%20for%20Functional%20Modules.pdf
first_indexed	2023-09-18T22:28:36Z
last_indexed	2023-09-18T22:28:36Z
_version_	1777416134136430592

A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network

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