Exploration of biological network centralities with CentiBiN

被引:156
作者
Junker, Bjoern H. [1 ]
Koschuetzki, Dirk [1 ]
Schreiber, Falk [1 ]
机构
[1] Leibniz Inst Plant Genet & Crop Plant Res, Dept Mol Genet, D-06466 Gatersleben, Germany
关键词
D O I
10.1186/1471-2105-7-219
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: The elucidation of whole-cell regulatory, metabolic, interaction and other biological networks generates the need for a meaningful ranking of network elements. Centrality analysis ranks network elements according to their importance within the network structure and different centrality measures focus on different importance concepts. Central elements of biological networks have been found to be, for example, essential for viability. Results: CentiBiN (Centralities in Biological Networks) is a tool for the computation and exploration of centralities in biological networks such as protein-protein interaction networks. It computes 17 different centralities for directed or undirected networks, ranging from local measures, that is, measures that only consider the direct neighbourhood of a network element, to global measures. CentiBiN supports the exploration of the centrality distribution by visualising central elements within the network and provides several layout mechanisms for the automatic generation of graphical representations of a network. It supports different input formats, especially for biological networks, and the export of the computed centralities to other tools. Conclusion: CentiBiN helps systems biology researchers to identify crucial elements of biological networks. CentiBiN including a user guide and example data sets is available free of charge at http://centibin.ipk-gatersleben.de/.CentiBiN is available in two different versions: a Java Web Start application and an installable Windows application.
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页数:7
相关论文
共 36 条
  • [1] Statistical mechanics of complex networks
    Albert, R
    Barabási, AL
    [J]. REVIEWS OF MODERN PHYSICS, 2002, 74 (01) : 47 - 97
  • [2] [Anonymous], PSYCHOMETRIKA
  • [3] [Anonymous], 2003, GENOME BIOL
  • [4] Emergence of scaling in random networks
    Barabási, AL
    Albert, R
    [J]. SCIENCE, 1999, 286 (5439) : 509 - 512
  • [5] Batagelj V, 2004, MATH VIS, P77
  • [6] Similarities and differences in genome-wide expression data of six organisms
    Bergmann, S
    Ihmels, J
    Barkai, N
    [J]. PLOS BIOLOGY, 2004, 2 (01) : 85 - 93
  • [7] FACTORING AND WEIGHTING APPROACHES TO STATUS SCORES AND CLIQUE IDENTIFICATION
    BONACICH, P
    [J]. JOURNAL OF MATHEMATICAL SOCIOLOGY, 1972, 2 (01) : 113 - 120
  • [8] BONACICH P, 1987, AM J SOCIOL, V92, P1170, DOI 10.1086/228631
  • [9] Brandes U, 2005, LECT NOTES COMPUT SC, V3404, P533
  • [10] Brandes U, 2002, LECT NOTES COMPUT SC, V2265, P501