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Diffusion Model Based Spectral Clustering for Protein-Protein Interaction Networks
http://hdl.handle.net/10228/5575
http://hdl.handle.net/10228/55757d4d28ec-6693-4232-b31a-155475ced720
| 名前 / ファイル | ライセンス | アクション |
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journal.pone.0012623.pdf (1.6 MB)
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| Item type | 学術雑誌論文 = Journal Article(1) | |||||||||||||
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| 公開日 | 2016-02-03 | |||||||||||||
| 資源タイプ | ||||||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||||||
| 資源タイプ | journal article | |||||||||||||
| タイトル | ||||||||||||||
| タイトル | Diffusion Model Based Spectral Clustering for Protein-Protein Interaction Networks | |||||||||||||
| 言語 | en | |||||||||||||
| 言語 | ||||||||||||||
| 言語 | eng | |||||||||||||
| 著者 |
Inoue, Kentaro
× Inoue, Kentaro× Li, Weijiang× 倉田, 博之
WEKO
2130
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| 抄録 | ||||||||||||||
| 内容記述タイプ | Abstract | |||||||||||||
| 内容記述 | BackgroundA goal of systems biology is to analyze large-scale molecular networks including gene expressions and protein-protein interactions, revealing the relationships between network structures and their biological functions. Dividing a protein-protein interaction (PPI) network into naturally grouped parts is an essential way to investigate the relationship between topology of networks and their functions. However, clear modular decomposition is often hard due to the heterogeneous or scale-free properties of PPI networks.Methodology/Principal FindingsTo address this problem, we propose a diffusion model-based spectral clustering algorithm, which analytically solves the cluster structure of PPI networks as a problem of random walks in the diffusion process in them. To cope with the heterogeneity of the networks, the power factor is introduced to adjust the diffusion matrix by weighting the transition (adjacency) matrix according to a node degree matrix. This algorithm is named adjustable diffusion matrix-based spectral clustering (ADMSC). To demonstrate the feasibility of ADMSC, we apply it to decomposition of a yeast PPI network, identifying biologically significant clusters with approximately equal size. Compared with other established algorithms, ADMSC facilitates clear and fast decomposition of PPI networks.Conclusions/SignificanceADMSC is proposed by introducing the power factor that adjusts the diffusion matrix to the heterogeneity of the PPI networks. ADMSC effectively partitions PPI networks into biologically significant clusters with almost equal sizes, while being very fast, robust and appealing simple. | |||||||||||||
| 言語 | en | |||||||||||||
| 書誌情報 |
en : PLoS ONE 巻 5, 号 9, p. e12623, 発行日 2010-09-07 |
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| 出版者 | Public Library of Science | |||||||||||||
| 言語 | en | |||||||||||||
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| 関連タイプ | isIdenticalTo | |||||||||||||
| 識別子タイプ | DOI | |||||||||||||
| 関連識別子 | https://doi.org/10.1371/journal.pone.0012623 | |||||||||||||
| ISSN | ||||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||||
| 収録物識別子 | 1932-6203 | |||||||||||||
| 著作権関連情報 | ||||||||||||||
| 権利情報 | Copyright (c) 2010 Inoue et al. | |||||||||||||
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| 権利情報 | This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |||||||||||||
| 出版タイプ | ||||||||||||||
| 出版タイプ | VoR | |||||||||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||||||||
| 査読の有無 | ||||||||||||||
| 値 | yes | |||||||||||||
| 研究者情報 | ||||||||||||||
| URL | https://hyokadb02.jimu.kyutech.ac.jp/html/265_ja.html | |||||||||||||
| 連携ID | ||||||||||||||
| 値 | 5312 | |||||||||||||
