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Bioinformatics Advance Access published online on October 4, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl488
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© 2006 The Author(s)
Received June 30, 2006
Revised August 25, 2006
Accepted September 15, 2006

Applications note

The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks

Kevin Y. Yip 1, Haiyuan Yu 2, Philip M. Kim 3, Martin Schultz 1, and Mark Gerstein 4 *

1 Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06511, USA
2 Department of Cancer Biology, Dana-Farber Cancer Institute, 1 Jimmy Fund Way, SM854, Boston, MA 02115, USA
3 Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Avenue, New Haven, CT 06520, USA
4 Department of Molecular Biophysics and Biochemistry, Yale University, 266 Whitney Avenue, New Haven, CT 06520, USA; Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06511, USA


  Abstract

Biological processes involve complex networks of interactions between molecules. Various large-scale experiments and curation efforts have led to preliminary versions of complete cellular networks for a number of organisms. To grapple with these networks, we developed tYNA, a Web system for managing, comparing and mining multiple networks, both directed and undirected. tYNA efficiently implements methods that have proven useful in network analysis, including identifying defective cliques, finding small network motifs (such as feed-forward loops), calculating global statistics (such as the clustering coefficient and eccentricity), and identifying hubs and bottlenecks. It also allows one to manage a large number of private and public networks using a flexible tagging system, to filter them based on a variety of criteria, and to visualize them through an interactive graphical interface. A number of commonly used biologically datasets have been pre-loaded into tYNA, standardized and grouped into different categories.

Availability: The tYNA system can be accessed at http://networks.gersteinlab.org/tyna. The source code, JavaDoc API, and WSDL can also be downloaded from the web site. tYNA can also be accessed from the Cytoscape software using a plugin.

Supplementary Information: Additional figures and tables can be found at http://networks.gersteinlab.org/tyna/supp.

Associate Editor: Chris Stoeckert
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