<?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%">Medina, I</style></author><author><style face="normal" font="default" size="100%">Tárraga, J</style></author><author><style face="normal" font="default" size="100%">Martínez, H</style></author><author><style face="normal" font="default" size="100%">Barrachina, S</style></author><author><style face="normal" font="default" size="100%">Castillo, M I</style></author><author><style face="normal" font="default" size="100%">Paschall, J</style></author><author><style face="normal" font="default" size="100%">Salavert-Torres, J</style></author><author><style face="normal" font="default" size="100%">Blanquer-Espert, I</style></author><author><style face="normal" font="default" size="100%">Hernández-García, V</style></author><author><style face="normal" font="default" size="100%">Quintana-Ortí, E S</style></author><author><style face="normal" font="default" size="100%">Dopazo, J</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Highly sensitive and ultrafast read mapping for RNA-seq analysis.</style></title><secondary-title><style face="normal" font="default" size="100%">DNA Res</style></secondary-title><alt-title><style face="normal" font="default" size="100%">DNA Res</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Genomics</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Sensitivity and Specificity</style></keyword><keyword><style  face="normal" font="default" size="100%">Sequence Analysis, RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Transcriptome</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016 Apr</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">23</style></volume><pages><style face="normal" font="default" size="100%">93-100</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;As sequencing technologies progress, the amount of data produced grows exponentially, shifting the bottleneck of discovery towards the data analysis phase. In particular, currently available mapping solutions for RNA-seq leave room for improvement in terms of sensitivity and performance, hindering an efficient analysis of transcriptomes by massive sequencing. Here, we present an innovative approach that combines re-engineering, optimization and parallelization. This solution results in a significant increase of mapping sensitivity over a wide range of read lengths and substantial shorter runtimes when compared with current RNA-seq mapping methods available.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/26740642?dopt=Abstract</style></custom1></record></records></xml>