01732nas a2200277   4500008004100000022001400041245009700055210006900152260001300221300001200234490000700246520083000253653002201083653003701105653002301142653001101165653001301176653003201189653001301221100001901234700001801253700002001271700002501291700002001316856011801336       2009                        eng d  a1362-496200aSNOW, a web-based tool for the statistical analysis of protein-protein interaction networks.0 aSNOW a webbased tool for the statistical analysis of proteinprot  c2009 Jul  aW109-140 v373 a<p>Understanding the structure and the dynamics of the complex intercellular network of interactions that contributes to the structure and function of a living cell is one of the main challenges of today's biology. SNOW inputs a collection of protein (or gene) identifiers and, by using the interactome as scaffold, draws the connections among them, calculates several relevant network parameters and, as a novelty among the rest of tools of its class, it estimates their statistical significance. The parameters calculated for each node are: connectivity, betweenness and clustering coefficient. It also calculates the number of components, number of bicomponents and articulation points. An interactive network viewer is also available to explore the resulting network. SNOW is available at http://snow.bioinfo.cipf.es.</p>10aComputer Graphics10aData Interpretation, Statistical10aDatabases, Protein10aHumans10aInternet10aProtein Interaction Mapping10aSoftware1 aMinguez, Pablo1 aGötz, Stefan1 aMontaner, David1 aAl-Shahrour, Fátima1 aDopazo, Joaquin  uhttp://clinbioinfosspa.es/content/snow-web-based-tool-statistical-analysis-protein-protein-interaction-networks-002717nas a2200385   4500008004100000022001400041245008300055210006900138260001300207300001200220490000700232520153300239653001201772653002601784653002201810653002301832653002801855653001001883653001301893653002701906653003101933653001301964653002701977100001802004700003302022700001802055700002102073700002902094700002402123700002302147700001802170700002002188700001602208856010702224       2008                        eng d  a1362-496200aHigh-throughput functional annotation and data mining with the Blast2GO suite.0 aHighthroughput functional annotation and data mining with the Bl  c2008 Jun  a3420-350 v363 a<p>Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologist-oriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) high-throughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data.</p>10aAnimals10aComputational Biology10aComputer Graphics10aDatabases, Genetic10aExpressed Sequence Tags10aGenes10aGenomics10aSequence Analysis, DNA10aSequence Analysis, Protein10aSoftware10aVocabulary, Controlled1 aGötz, Stefan1 aGarcía-Gómez, Juan, Miguel1 aTerol, Javier1 aWilliams, Tim, D1 aNagaraj, Shivashankar, H1 aNueda, Maria, José1 aRobles, Montserrat1 aTalon, Manuel1 aDopazo, Joaquin1 aConesa, Ana  uhttp://clinbioinfosspa.es/content/high-throughput-functional-annotation-and-data-mining-blast2go-suite