empirical comparison of visualization tools for larger-scale network analysis
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ID: 175865
2017
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Abstract
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.
| Reference Key |
pavlopoulos2017advancesempirical
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|---|---|
| Authors | ;Georgios A. Pavlopoulos;David Paez-Espino;Nikos C. Kyrpides;Ioannis Iliopoulos |
| Journal | journal of hepatocellular carcinoma |
| Year | 2017 |
| DOI |
10.1155/2017/1278932
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| URL | |
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