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Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis
Author(s) -
Georgios A. Pavlopoulos,
David Páez-Espino,
Nikos C. Kyrpides,
Ioannis Iliopoulos
Publication year - 2017
Publication title -
advances in bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.33
H-Index - 20
eISSN - 1687-8035
pISSN - 1687-8027
DOI - 10.1155/2017/1278932
Subject(s) - computer science , visualization , scale (ratio) , data science , data mining , cartography , geography
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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