<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Ana Rita Grosso</style></author><author><style face="normal" font="default" size="100%">Gomes, Anita Q</style></author><author><style face="normal" font="default" size="100%">Barbosa-Morais, Nuno L.</style></author><author><style face="normal" font="default" size="100%">Caldeira, Sandra</style></author><author><style face="normal" font="default" size="100%">Thorne, Natalie P.</style></author><author><style face="normal" font="default" size="100%">Grech, Godfrey</style></author><author><style face="normal" font="default" size="100%">von Lindern, Marieke</style></author><author><style face="normal" font="default" size="100%">Carmo-fonseca, Maria</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Tissue-specific splicing factor gene expression signatures</style></title><secondary-title><style face="normal" font="default" size="100%">Nucl. Acids Res.</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Alternative Splicing</style></keyword><keyword><style  face="normal" font="default" size="100%">analysis/metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Animals</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Differentiatio</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Differentiation</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Differentiation: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Line</style></keyword><keyword><style  face="normal" font="default" size="100%">Computational Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">genetics/metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Messenger</style></keyword><keyword><style  face="normal" font="default" size="100%">Messenger: analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Messenger: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Mice</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Pan troglodytes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pan troglodytes: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA-Binding Proteins</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA-Binding Proteins: genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA-Binding Proteins: metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Tissue Distribution</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1093/nar/gkn463</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">15</style></number><publisher><style face="normal" font="default" size="100%">Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal.</style></publisher><volume><style face="normal" font="default" size="100%">36</style></volume><pages><style face="normal" font="default" size="100%">4823–4832</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The alternative splicing code that controls and coordinates the transcriptome in complex multicellular organisms remains poorly understood. It has long been argued that regulation of alternative splicing relies on combinatorial interactions between multiple proteins, and that tissue-specific splicing decisions most likely result from differences in the concentration and/or activity of these proteins. However, large-scale data to systematically address this issue have just recently started to become available. Here we show that splicing factor gene expression signatures can be identified that reflect cell type and tissue-specific patterns of alternative splicing. We used a computational approach to analyze microarray-based gene expression profiles of splicing factors from mouse, chimpanzee and human tissues. Our results show that brain and testis, the two tissues with highest levels of alternative splicing events, have the largest number of splicing factor genes that are most highly differentially expressed. We further identified SR protein kinases and small nuclear ribonucleoprotein particle (snRNP) proteins among the splicing factor genes that are most highly differentially expressed in a particular tissue. These results indicate the power of generating signature-based predictions as an initial computational approach into a global view of tissue-specific alternative splicing regulation.&lt;/p&gt;
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