<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Lorente-Galdos, Belén</style></author><author><style face="normal" font="default" size="100%">Medina, Ignacio</style></author><author><style face="normal" font="default" size="100%">Morcillo-Suarez, Carlos</style></author><author><style face="normal" font="default" size="100%">Heredia, Txema</style></author><author><style face="normal" font="default" size="100%">Carreño-Torres, Angel</style></author><author><style face="normal" font="default" size="100%">Sangrós, Ricardo</style></author><author><style face="normal" font="default" size="100%">Alegre, Josep</style></author><author><style face="normal" font="default" size="100%">Pita, Guillermo</style></author><author><style face="normal" font="default" size="100%">Vellalta, Gemma</style></author><author><style face="normal" font="default" size="100%">Malats, Nuria</style></author><author><style face="normal" font="default" size="100%">Pisano, David G</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author><author><style face="normal" font="default" size="100%">Navarro, Arcadi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Select your SNPs (SYSNPs): a web tool for automatic and massive selection of SNPs.</style></title><secondary-title><style face="normal" font="default" size="100%">International journal of data mining and bioinformatics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2012</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2012</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://inderscience.metapress.com/content/f76740x8071u513n/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">6</style></volume><pages><style face="normal" font="default" size="100%">324-34</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Association studies are the choice approach in the discovery of the genomic basis of complex traits. To carry out such analysis, researchers frequently need to (1) select optimally informative sets of Single Nucleotide Polymorphisms (SNPs) in candidate regions and (2) annotate the results of associations found by means of genome-wide SNP arrays. These are complex tasks, since many criteria have to be considered, including the SNPs’ functional properties, technological information and haplotype frequencies in given populations. SYSNPs implements algorithms that allow for efficient and simultaneous consideration of all the relevant criteria to obtain sets of SNPs that properly cover arbitrarily large lists of genes or genomic regions. Complementarily, SYSNPs allows for comprehensive functional annotation of SNPs linked to any given marker SNP. SYSNPs dramatically reduces the effort needed for SNP selection from days of searching various databases to a few minutes using a simple browser.</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marigorta, Urko M</style></author><author><style face="normal" font="default" size="100%">Lao, Oscar</style></author><author><style face="normal" font="default" size="100%">Casals, Ferran</style></author><author><style face="normal" font="default" size="100%">Calafell, Francesc</style></author><author><style face="normal" font="default" size="100%">Morcillo-Suarez, Carlos</style></author><author><style face="normal" font="default" size="100%">Faria, Rui</style></author><author><style face="normal" font="default" size="100%">Bosch, Elena</style></author><author><style face="normal" font="default" size="100%">Serra, François</style></author><author><style face="normal" font="default" size="100%">Bertranpetit, Jaume</style></author><author><style face="normal" font="default" size="100%">Dopazo, Hernán</style></author><author><style face="normal" font="default" size="100%">Navarro, Arcadi</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Recent human evolution has shaped geographical differences in susceptibility to disease.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC genomics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2011</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2011</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">55</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Searching for associations between genetic variants and complex diseases has been a very active area of research for over two decades. More than 51,000 potential associations have been studied and published, a figure that keeps increasing, especially with the recent explosion of array-based Genome-Wide Association Studies. Even if the number of true associations described so far is high, many of the putative risk variants detected so far have failed to be consistently replicated and are widely considered false positives. Here, we focus on the world-wide patterns of replicability of published association studies.&lt;/p&gt;</style></abstract></record></records></xml>