Semi-bipartite graph visualization for gene ontology networks
Paper
Paper/Presentation Title | Semi-bipartite graph visualization for gene ontology networks |
---|---|
Presentation Type | Paper |
Authors | Xu, Kai (Author), Williams, Rohan (Author), Hong, Seok-Hee (Author), Liu, Qing (Author) and Zhang, Ji (Author) |
Editors | Eppstein, D. and Gansner, E. R. |
Journal or Proceedings Title | Lecture Notes in Computer Science (Book series) |
Journal Citation | 5849, pp. 244-255 |
Number of Pages | 12 |
Year | 2010 |
Publisher | Springer |
Place of Publication | Heidelberg, Germany |
ISSN | 1611-3349 |
0302-9743 | |
ISBN | 9783642118043 |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-642-11805-0_24 |
Web Address (URL) of Paper | http://www.springerlink.com/content/y41046p205475457/fulltext.pdf |
Conference/Event | GD 2009: 17th International Symposium on Graph Drawing |
Event Details | GD 2009: 17th International Symposium on Graph Drawing Event Date 22 to end of 25 Sep 2009 Event Location Chicago, United States |
Abstract | In this paper we propose three layout algorithms for semi-bipartite graphs-bipartite graphs with edges in one partition-that emerge from microarray experiment analysis. We also introduce a method that effectively reduces visual complexity by removing less informative nodes. The drawing quality and running time are evaluated with five real-world datasets, and the results show significant reduction in crossing number and total edge length. All the proposed methods are available in visualization package GEOMI, and are well received by domain users. |
Keywords | semi-bipartite graphs; bipartite graphs; gene ontology networks |
ANZSRC Field of Research 2020 | 469999. Other information and computing sciences not elsewhere classified |
321103. Cancer genetics | |
310505. Gene expression (incl. microarray and other genome-wide approaches) | |
Public Notes | File reproduced in accordance with the copyright policy of the publisher/author. |
Byline Affiliations | Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia |
Australian National University | |
University of Sydney | |
Centre for Systems Biology |
https://research.usq.edu.au/item/9z365/semi-bipartite-graph-visualization-for-gene-ontology-networks
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