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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8173


    Title: Hierarchical structure of the protein-protein interaction networks
    Authors: K.L. Ng;P.H. Lee;C.H. Huang;J.F. Fang;H.W. Hsiao;Jeffery J.P. Tsai
    Contributors: Department of Bioinformatics
    Date: 2006-02
    Issue Date: 2010-03-19 16:25:15 (UTC+8)
    Publisher: Asia University
    Abstract: We employed the random graph theory approach to analyze data for seven species in the
    protein-protein interaction database DIP. Several global topological parameters were used
    to characterize the protein-protein interaction networks (PINs) for each species. The plots
    of the logarithm of the node degree cumulative distribution Pcum(k) vs. the logarithm of
    node degree k indicates that PINs follow the power law (Pcum(k) k? ). Good evidence by
    correlation analysis supports the fact that the seven PINs are well approximated by scale-free
    networks. We found that the logarithm of Cave(k) scales with k (i.e. Cave(k) k? ) for
    E. coli and yeast. In particular, we determine that the E. coli and the yeast PINs are well
    represented by the stochastic and deterministic hierarchical network models, respectively.
    These results suggest that the hierarchical network model is a good description for certain
    species’ PINs, but this may not be a universal feature across different species.
    Relation: Chinese Journal of Physics 44(1): 67-77
    Appears in Collections:[生物資訊與醫學工程學系 ] 期刊論文

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