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Title: 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. Lastly, we comment on their strengths and their weaknesses and empirically discuss their scalability, user friendliness, and postvisualization capabilities.
Authors:
ORCiD logo [1] ;  [1] ;  [1] ; ORCiD logo [2]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)
  2. Univ. of Crete Medical School, Heraklion (Greece). Division of Basic Sciences
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Published Article
Journal Name:
Advances in Bioinformatics
Additional Journal Information:
Journal Volume: 2017; Related Information: CHORUS Timestamp: 2017-07-18 17:02:10; Journal ID: ISSN 1687-8027
Publisher:
Hindawi Publishing Corporation
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
Country unknown/Code not available
Language:
English
OSTI Identifier:
1371813