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dc.contributor.authorHu, Zhenjunen_US
dc.contributor.authorHung, Jui-Hungen_US
dc.contributor.authorWang, Yanen_US
dc.contributor.authorChang, Yi-Chienen_US
dc.contributor.authorHuang, Chia-Lingen_US
dc.contributor.authorHuyck, Matten_US
dc.contributor.authorDeLisi, Charlesen_US
dc.date.accessioned2012-01-11T00:40:03Z
dc.date.available2012-01-11T00:40:03Z
dc.date.copyright2009
dc.date.issued2009-7-1
dc.identifier.citationHu, Zhenjun, Jui-Hung Hung, Yan Wang, Yi-Chien Chang, Chia-Ling Huang, Matt Huyck, Charles DeLisi. "VisANT 3.5: multi-scale network visualization, analysis and inference based on the gene ontology" Nucleic Acids Research 37(Web Server issue): W115-W121. (2009)
dc.identifier.issn1362-4962
dc.identifier.urihttps://hdl.handle.net/2144/3031
dc.description.abstractDespite its wide usage in biological databases and applications, the role of the gene ontology (GO) in network analysis is usually limited to functional annotation of genes or gene sets with auxiliary information on correlations ignored. Here, we report on new capabilities of VisANT—an integrative software platform for the visualization, mining, analysis and modeling of the biological networks—which extend the application of GO in network visualization, analysis and inference. The new VisANT functions can be classified into three categories. (i) Visualization: a new tree-based browser allows visualization of GO hierarchies. GO terms can be easily dropped into the network to group genes annotated under the term, thereby integrating the hierarchical ontology with the network. This facilitates multi-scale visualization and analysis. (ii) Flexible annotation schema: in addition to conventional methods for annotating network nodes with the most specific functional descriptions available, VisANT also provides functions to annotate genes at any customized level of abstraction. (iii) Finding over-represented GO terms and expression-enriched GO modules: two new algorithms have been implemented as VisANT plugins. One detects over-represented GO annotations in any given sub-network and the other finds the GO categories that are enriched in a specified phenotype or perturbed dataset. Both algorithms take account of network topology (i.e. correlations between genes based on various sources of evidence). VisANT is freely available at http://visant.bu.edu.en_US
dc.description.sponsorshipNational Institutes of Health (1R01RR022971-01A1, 1R21CA135882-01)en_US
dc.language.isoen
dc.rightsCopyright 2009 Hu, Zhenjun, Jui-Hung Hung, Yan Wang, Yi-Chien Chang, Chia-Ling Huang, Matt Huyck, Charles DeLisien_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc/2.0/uk/
dc.titleVisANT 3.5: Multi-Scale Network Visualization, Analysis and Inference Based on the Gene Ontologyen_US
dc.typeArticleen_US
dc.identifier.doi10.1093/nar/gkp406
dc.identifier.pmid19465394
dc.identifier.pmcid2703932


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Copyright 2009 Hu, Zhenjun, Jui-Hung Hung, Yan Wang, Yi-Chien Chang, Chia-Ling Huang, Matt Huyck, Charles DeLisi
Except where otherwise noted, this item's license is described as Copyright 2009 Hu, Zhenjun, Jui-Hung Hung, Yan Wang, Yi-Chien Chang, Chia-Ling Huang, Matt Huyck, Charles DeLisi