<?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%">Olanda, Ricardo</style></author><author><style face="normal" font="default" size="100%">Pérez, Mariano</style></author><author><style face="normal" font="default" size="100%">Orduña, Juan M</style></author><author><style face="normal" font="default" size="100%">Tárraga, Joaquín</style></author><author><style face="normal" font="default" size="100%">Joaquín Dopazo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A new parallel pipeline for DNA methylation analysis of long reads datasets.</style></title><secondary-title><style face="normal" font="default" size="100%">BMC bioinformatics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Methyl-Seq</style></keyword><keyword><style  face="normal" font="default" size="100%">NGS</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017 Mar 09</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1574-3</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">18</style></volume><pages><style face="normal" font="default" size="100%">161</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">BACKGROUND: DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis have been proposed over recent years. However, the current trend is that the new sequencers and the ones expected for an upcoming future yield sequences of increasing length, making these software tools inefficient and obsolete. RESULTS: In this paper, we propose a new software based on a strategy for methylation analysis of Methyl-seq sequencing data that requires much shorter execution times while yielding a better level of sensitivity, particularly for datasets composed of long reads. This strategy can be exported to other methylation, DNA and RNA analysis tools. CONCLUSIONS: The developed software tool achieves execution times one order of magnitude shorter than the existing tools, while yielding equal sensitivity for short reads and even better sensitivity for long reads.</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%">Carmona, F Javier</style></author><author><style face="normal" font="default" size="100%">Davalos, Veronica</style></author><author><style face="normal" font="default" size="100%">Vidal, Enrique</style></author><author><style face="normal" font="default" size="100%">Gomez, Antonio</style></author><author><style face="normal" font="default" size="100%">Heyn, Holger</style></author><author><style face="normal" font="default" size="100%">Hashimoto, Yutaka</style></author><author><style face="normal" font="default" size="100%">Vizoso, Miguel</style></author><author><style face="normal" font="default" size="100%">Martinez-Cardus, Anna</style></author><author><style face="normal" font="default" size="100%">Sayols, Sergi</style></author><author><style face="normal" font="default" size="100%">Ferreira, Humberto</style></author><author><style face="normal" font="default" size="100%">Sanchez-Mut, Jose</style></author><author><style face="normal" font="default" size="100%">Moran, Sebastian</style></author><author><style face="normal" font="default" size="100%">Margeli, Mireia</style></author><author><style face="normal" font="default" size="100%">Castella, Eva</style></author><author><style face="normal" font="default" size="100%">Berdasco, Maria</style></author><author><style face="normal" font="default" size="100%">Stefansson, Olafur Andri</style></author><author><style face="normal" font="default" size="100%">Eyfjord, Jorunn E</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Suarez, Eva</style></author><author><style face="normal" font="default" size="100%">Dopazo, Joaquin</style></author><author><style face="normal" font="default" size="100%">Orozco, Modesto</style></author><author><style face="normal" font="default" size="100%">Gut, Ivo</style></author><author><style face="normal" font="default" size="100%">Esteller, Manel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A Comprehensive DNA Methylation Profile of Epithelial-to-Mesenchymal Transition.</style></title><secondary-title><style face="normal" font="default" size="100%">Cancer research</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Methyl-Seq</style></keyword><keyword><style  face="normal" font="default" size="100%">Methylomics</style></keyword><keyword><style  face="normal" font="default" size="100%">Next Generation Sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2014 Aug 8</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/pubmed/25106427</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">19</style></number><volume><style face="normal" font="default" size="100%">74</style></volume><pages><style face="normal" font="default" size="100%">5608–19</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Epithelial-to-mesenchymal transition (EMT) is a plastic process in which fully differentiated epithelial cells are converted into poorly differentiated, migratory and invasive mesenchymal cells and it has been related to the metastasis potential of tumors. This is a reversible process and cells can also eventually undergo mesenchymal-to-epithelial transition (MET). The existence of a dynamic EMT process suggests the involvement of epigenetic shifts in the phenotype. Herein, we obtained the DNA methylomes at single-base resolution of MDCK cells undergoing epithelial-to-mesenchymal transition (EMT) and translated the identified differentially methylated regions (DMRs) to human breast cancer cells undergoing a gain of migratory and invasive capabilities associated with the EMT phenotype. We noticed dynamic and reversible changes of DNA methylation, both on promoter sequences and gene-bodies in association with transcription regulation of EMT-related genes. Most importantly, the identified DNA methylation markers of EMT were present in primary mammary tumors in association with the epithelial or the mesenchymal phenotype of the studied breast cancer samples.</style></abstract></record></records></xml>