Detection of functional modules from protein interaction networks with an enhanced random walk based algorithm

    Research output: Contribution to journalArticle

    Abstract

    In this paper, we propose a new random walk-based clustering algorithm for detecting functional modules in protein-protein interaction (PPI) networks. It has been tested on two yeast PPI networks. Greater precision, better homogeneity and higher modularity were achieved in comparison with the results produced by the recently developed RRW clustering technique and the well-known CFinder algorithm. A much higher level of true positives were observed in the clustering results. The analysis indicated that the proposed method can not only detect overlapping modules but also be potentially used to identify functional modules with different topological structures, which may not be highly connected.

    LanguageEnglish
    Pages290-306
    Number of pages17
    JournalInternational Journal of Computational Biology and Drug Design
    Volume4
    Issue number3
    Early online date21 Jul 2011
    DOIs
    Publication statusPublished - 31 Jul 2011

    Fingerprint

    Protein Interaction Maps
    Cluster Analysis
    Proteins
    Fungal Proteins
    Clustering algorithms

    Keywords

    • Graph clustering
    • PPIs
    • Protein-protein interactions
    • Random walks

    Cite this

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    title = "Detection of functional modules from protein interaction networks with an enhanced random walk based algorithm",
    abstract = "In this paper, we propose a new random walk-based clustering algorithm for detecting functional modules in protein-protein interaction (PPI) networks. It has been tested on two yeast PPI networks. Greater precision, better homogeneity and higher modularity were achieved in comparison with the results produced by the recently developed RRW clustering technique and the well-known CFinder algorithm. A much higher level of true positives were observed in the clustering results. The analysis indicated that the proposed method can not only detect overlapping modules but also be potentially used to identify functional modules with different topological structures, which may not be highly connected.",
    keywords = "Graph clustering, PPIs, Protein-protein interactions, Random walks",
    author = "Bingjing Cai and Haiying Wang and Huiru Zheng and Hui Wang",
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    AU - Wang, Haiying

    AU - Zheng, Huiru

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    AB - In this paper, we propose a new random walk-based clustering algorithm for detecting functional modules in protein-protein interaction (PPI) networks. It has been tested on two yeast PPI networks. Greater precision, better homogeneity and higher modularity were achieved in comparison with the results produced by the recently developed RRW clustering technique and the well-known CFinder algorithm. A much higher level of true positives were observed in the clustering results. The analysis indicated that the proposed method can not only detect overlapping modules but also be potentially used to identify functional modules with different topological structures, which may not be highly connected.

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