大规模网络分析可视化工具的实证比较。

Q1 Biochemistry, Genetics and Molecular Biology
Advances in Bioinformatics Pub Date : 2017-01-01 Epub Date: 2017-07-18 DOI:10.1155/2017/1278932
Georgios A Pavlopoulos, David Paez-Espino, Nikos C Kyrpides, Ioannis Iliopoulos
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引用次数: 50

摘要

基因表达、信号转导、蛋白质/化学相互作用、生物医学文献共发生和其他概念经常被捕获在生物网络表示中,其中节点代表某个生物实体,并将它们之间的连接边缘。虽然已经存在许多工具来操纵、可视化和交互式地探索这些网络,但只有少数工具可以扩大规模,并跟上当今无可争议的信息增长。在这篇综述中,我们简要列出了可用的网络可视化工具的目录,从用户体验的角度来看,我们确定了四种适合大规模网络分析、可视化和探索的候选工具。我们评论了它们的优点和缺点,并经验地讨论了它们的可伸缩性、用户友好性和后可视化功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis.

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis.

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis.

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis.

Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today's indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. We comment on their strengths and their weaknesses and empirically discuss their scalability, user friendliness, and postvisualization capabilities.

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来源期刊
Advances in Bioinformatics
Advances in Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (miscellaneous)
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