ABC and IFC: Modules Detection Method for PPI Network

Many clustering algorithms are unable to solve the clustering problem of protein-protein interaction (PPI) networks effectively. A novel clustering model which combines the optimization mechanism of artificial bee colony (ABC) with the fuzzy membership matrix is proposed in this paper. The proposed...

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Detalles Bibliográficos
Autores principales: Lei, Xiujuan, Wu, Fang-Xiang, Tian, Jianfang, Zhao, Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4060787/
https://www.ncbi.nlm.nih.gov/pubmed/24991575
http://dx.doi.org/10.1155/2014/968173
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author Lei, Xiujuan
Wu, Fang-Xiang
Tian, Jianfang
Zhao, Jie
author_facet Lei, Xiujuan
Wu, Fang-Xiang
Tian, Jianfang
Zhao, Jie
author_sort Lei, Xiujuan
collection PubMed
description Many clustering algorithms are unable to solve the clustering problem of protein-protein interaction (PPI) networks effectively. A novel clustering model which combines the optimization mechanism of artificial bee colony (ABC) with the fuzzy membership matrix is proposed in this paper. The proposed ABC-IFC clustering model contains two parts: searching for the optimum cluster centers using ABC mechanism and forming clusters using intuitionistic fuzzy clustering (IFC) method. Firstly, the cluster centers are set randomly and the initial clustering results are obtained by using fuzzy membership matrix. Then the cluster centers are updated through different functions of bees in ABC algorithm; then the clustering result is obtained through IFC method based on the new optimized cluster center. To illustrate its performance, the ABC-IFC method is compared with the traditional fuzzy C-means clustering and IFC method. The experimental results on MIPS dataset show that the proposed ABC-IFC method not only gets improved in terms of several commonly used evaluation criteria such as precision, recall, and P value, but also obtains a better clustering result.
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spelling pubmed-40607872014-07-02 ABC and IFC: Modules Detection Method for PPI Network Lei, Xiujuan Wu, Fang-Xiang Tian, Jianfang Zhao, Jie Biomed Res Int Research Article Many clustering algorithms are unable to solve the clustering problem of protein-protein interaction (PPI) networks effectively. A novel clustering model which combines the optimization mechanism of artificial bee colony (ABC) with the fuzzy membership matrix is proposed in this paper. The proposed ABC-IFC clustering model contains two parts: searching for the optimum cluster centers using ABC mechanism and forming clusters using intuitionistic fuzzy clustering (IFC) method. Firstly, the cluster centers are set randomly and the initial clustering results are obtained by using fuzzy membership matrix. Then the cluster centers are updated through different functions of bees in ABC algorithm; then the clustering result is obtained through IFC method based on the new optimized cluster center. To illustrate its performance, the ABC-IFC method is compared with the traditional fuzzy C-means clustering and IFC method. The experimental results on MIPS dataset show that the proposed ABC-IFC method not only gets improved in terms of several commonly used evaluation criteria such as precision, recall, and P value, but also obtains a better clustering result. Hindawi Publishing Corporation 2014 2014-06-02 /pmc/articles/PMC4060787/ /pubmed/24991575 http://dx.doi.org/10.1155/2014/968173 Text en Copyright © 2014 Xiujuan Lei et al. https://creativecommons.org/licenses/by/3.0/ 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.
spellingShingle Research Article
Lei, Xiujuan
Wu, Fang-Xiang
Tian, Jianfang
Zhao, Jie
ABC and IFC: Modules Detection Method for PPI Network
title ABC and IFC: Modules Detection Method for PPI Network
title_full ABC and IFC: Modules Detection Method for PPI Network
title_fullStr ABC and IFC: Modules Detection Method for PPI Network
title_full_unstemmed ABC and IFC: Modules Detection Method for PPI Network
title_short ABC and IFC: Modules Detection Method for PPI Network
title_sort abc and ifc: modules detection method for ppi network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4060787/
https://www.ncbi.nlm.nih.gov/pubmed/24991575
http://dx.doi.org/10.1155/2014/968173
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