{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Carazo F"],"funding":["Eusko Jaurlaritza","Provincial Council of Gipuzkoa"],"pagination":["521"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6592009"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["20(1)"],"pubmed_abstract":["<h4>Background</h4>Splicing is a genetic process that has important implications in several diseases including cancer. Deciphering the complex rules of splicing regulation is crucial to understand and treat splicing-related diseases. Splicing factors and other RNA-binding proteins (RBPs) play a key role in the regulation of splicing. The specific binding sites of an RBP can be measured using CLIP experiments. However, to unveil which RBPs regulate a condition, it is necessary to have a priori hypotheses, as a single CLIP experiment targets a single protein.<h4>Results</h4>In this work, we present a novel methodology to predict context-specific splicing factors from transcriptomic data. For this, we systematically collect, integrate and analyze more than 900 CLIP experiments stored in four "],"journal":["BMC genomics"],"pubmed_title":["Integration of CLIP experiments of RNA-binding proteins: a novel approach to predict context-dependent splicing factors from transcriptomic data."],"pmcid":["PMC6592009"],"funding_grant_id":["MINEDRUG project: “Predicting therapy response in oncology using Big Data analysis&quot;","MINEDRUG project: \"Predicting therapy response in oncology using Big Data analysis\"","PRE_2017_2_0033"],"pubmed_authors":["Ferrer-Bonsoms JA","Rubio A","Carazo F","Gimeno M"],"additional_accession":[]},"is_claimable":false,"name":"Integration of CLIP experiments of RNA-binding proteins: a novel approach to predict context-dependent splicing factors from transcriptomic data.","description":"<h4>Background</h4>Splicing is a genetic process that has important implications in several diseases including cancer. Deciphering the complex rules of splicing regulation is crucial to understand and treat splicing-related diseases. Splicing factors and other RNA-binding proteins (RBPs) play a key role in the regulation of splicing. The specific binding sites of an RBP can be measured using CLIP experiments. However, to unveil which RBPs regulate a condition, it is necessary to have a priori hypotheses, as a single CLIP experiment targets a single protein.<h4>Results</h4>In this work, we present a novel methodology to predict context-specific splicing factors from transcriptomic data. For this, we systematically collect, integrate and analyze more than 900 CLIP experiments stored in four ","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019 Jun","modification":"2025-05-18T11:02:44.26Z","creation":"2025-05-18T11:02:44.26Z"},"accession":"S-EPMC6592009","cross_references":{"pubmed":["31238884"],"doi":["10.1186/s12864-019-5900-1"]}}