中心性
计算机科学
计算生物学
数据挖掘
蛋白质相互作用网络
插件
数据科学
蛋白质-蛋白质相互作用
数学
生物
统计
遗传学
程序设计语言
作者
Yu Tang,Min Li,Jianxin Wang,Yi Pan,Fang‐Xiang Wu
出处
期刊:BioSystems
[Elsevier BV]
日期:2014-11-17
卷期号:127: 67-72
被引量:1100
标识
DOI:10.1016/j.biosystems.2014.11.005
摘要
Nowadays, centrality analysis has become a principal method for identifying essential proteins in biological networks. Here we present CytoNCA, a Cytoscape plugin integrating calculation, evaluation and visualization analysis for multiple centrality measures. (i) CytoNCA supports eight different centrality measures and each can be applied to both weighted and unweighted biological networks. (ii) It allows users to upload biological information of both nodes and edges in the network, to integrate biological data with topological data to detect specific nodes. (iii) CytoNCA offers multiple potent visualization analysis modules, which generate various forms of output such as graph, table, and chart, and analyze associations among all measures. (iv) It can be utilized to quantitatively assess the calculation results, and evaluate the accuracy by statistical measures. (v) Besides current eight centrality measures, the biological characters from other sources could also be analyzed and assessed by CytoNCA. This makes CytoNCA an excellent tool for calculating centrality, evaluating and visualizing biological networks. http://apps.cytoscape.org/apps/cytonca.
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