CINNA: an R/CRAN package to decipher Central Informative Nodes in Network Analysis

被引:26
作者
Ashtiani, Minoo [1 ]
Mirzaie, Mehdi [2 ]
Jafari, Mohieddin [1 ,3 ]
机构
[1] Pasteur Inst Iran, Med Biotechnol Dept, Biotechnol Res Ctr, Tehran 1316943551, Iran
[2] Tarbiat Modares Univ, Fac Math Sci, Dept Appl Math, Tehran 14115134, Iran
[3] Univ Helsinki, Helsinki Inst Life Sci, Inst Mol Med Finland FIMM, FIN-00014 Helsinki, Finland
关键词
D O I
10.1093/bioinformatics/bty819
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Motivation: Centrality analysis involves a series of ambiguities in that there are numerous well-known centrality measures with differing algorithms for establishing which nodes in a network are essential. There is no clearly preferred measure or means of deciding which measure is most germane to a given network with respect to node essentiality vis-a-vis topological features. Our aim here was to develop an instrument that enables comparisons among potentially appropriate centrality measures to be made with respect to network structure and thereby to support the identification of the most informative measure according to dimensional reduction methods. Methods: The Central Informative Nodes in Network Analysis (CINNA) package introduced herein gathers all required functions for centrality analysis in weighted/unweighted and directed/undirected networks. Then, it compares, assorts and visualizes centrality measures to select which best describes the node importance. Availability and implementation: CINNA is available in CRAN, including a tutorial. URL: https://cran.r-project.org/web/packages/CINNA/index.html.
引用
收藏
页码:1436 / 1437
页数:2
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