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

@article{citeulike:1241006, 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 TopNet-like Yale Network Analyzer (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 biological 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 website. tYNA can also be accessed from the Cytoscape software using a plugin.}, address = {Department of Computer Science, Yale University, New Haven, CT 06511, USA.}, author = {Yip, K. Y. and Yu, H. and Kim, P. M. and Schultz, M. and Gerstein, M.}, citeulike-article-id = {1241006}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/17021160}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=17021160}, citeulike-linkout-2 = {http://dx.doi.org/10.1093/bioinformatics/btl488}, day = {1}, doi = {10.1093/bioinformatics/btl488}, issn = {1460-2059}, journal = {Bioinformatics}, keywords = {network-analysis, software}, month = {December}, number = {23}, pages = {2968--2970}, posted-at = {2007-04-21 07:11:02}, priority = {2}, title = {The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks.}, url = {http://dx.doi.org/10.1093/bioinformatics/btl488}, volume = {22}, year = {2006} }

TY - JOUR ID - citeulike:1241006 L3 - citeulike-article-id:1241006 N2 - 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 TopNet-like Yale Network Analyzer (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 biological 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 website. tYNA can also be accessed from the Cytoscape software using a plugin. IS - 23 JF - Bioinformatics SN - 1460-2059 AD - Department of Computer Science, Yale University, New Haven, CT 06511, USA. EP - 2970 TI - The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks. VL - 22 SP - 2968 KW - network-analysis KW - software AU - Yip, KY AU - Yu, H AU - Kim, PM AU - Schultz, M AU - Gerstein, M PY - 2006/12/01/ UR - http://dx.doi.org/10.1093/bioinformatics/btl488 ER -