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Article: Computational identification of protein binding sites on RNAs using high-throughput RNA structure-probing data

TitleComputational identification of protein binding sites on RNAs using high-throughput RNA structure-probing data
Authors
Issue Date2014
PublisherOxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/
Citation
Bioinformatics, 2014, v. 30 n. 8, p. 1049-1055 How to Cite?
AbstractMOTIVATION: High-throughput sequencing has been used to probe RNA structures, by treating RNAs with reagents that preferentially cleave or mark certain nucleotides according to their local structures, followed by sequencing of the resulting fragments. The data produced contain valuable information for studying various RNA properties. RESULTS: We developed methods for statistically modeling these structure-probing data and extracting structural features from them. We show that the extracted features can be used to predict RNA 'zipcodes' in yeast, regions bound by the She complex in asymmetric localization. The prediction accuracy was better than using raw RNA probing data or sequence features. We further demonstrate the use of the extracted features in identifying binding sites of RNA binding proteins from whole-transcriptome global photoactivatable-ribonucleoside-enhanced cross-linking and immunopurification (gPAR-CLIP) data.
Persistent Identifierhttp://hdl.handle.net/10722/204715
ISSN
2015 Impact Factor: 5.766
2015 SCImago Journal Rankings: 4.643

 

DC FieldValueLanguage
dc.contributor.authorHu, XH-
dc.contributor.authorWong, TKF-
dc.contributor.authorLu, ZJ-
dc.contributor.authorChan, TF-
dc.contributor.authorLau, TCK-
dc.contributor.authorYiu, SM-
dc.contributor.authorYip, KY-
dc.date.accessioned2014-09-20T00:31:40Z-
dc.date.available2014-09-20T00:31:40Z-
dc.date.issued2014-
dc.identifier.citationBioinformatics, 2014, v. 30 n. 8, p. 1049-1055-
dc.identifier.issn1367-4803-
dc.identifier.urihttp://hdl.handle.net/10722/204715-
dc.description.abstractMOTIVATION: High-throughput sequencing has been used to probe RNA structures, by treating RNAs with reagents that preferentially cleave or mark certain nucleotides according to their local structures, followed by sequencing of the resulting fragments. The data produced contain valuable information for studying various RNA properties. RESULTS: We developed methods for statistically modeling these structure-probing data and extracting structural features from them. We show that the extracted features can be used to predict RNA 'zipcodes' in yeast, regions bound by the She complex in asymmetric localization. The prediction accuracy was better than using raw RNA probing data or sequence features. We further demonstrate the use of the extracted features in identifying binding sites of RNA binding proteins from whole-transcriptome global photoactivatable-ribonucleoside-enhanced cross-linking and immunopurification (gPAR-CLIP) data.-
dc.languageeng-
dc.publisherOxford University Press. The Journal's web site is located at http://bioinformatics.oxfordjournals.org/-
dc.relation.ispartofBioinformatics-
dc.titleComputational identification of protein binding sites on RNAs using high-throughput RNA structure-probing data-
dc.typeArticle-
dc.identifier.emailYiu, SM: smyiu@cs.hku.hk-
dc.identifier.authorityYiu, SM=rp00207-
dc.identifier.doi10.1093/bioinformatics/btt757-
dc.identifier.pmid24376038-
dc.identifier.hkuros238672-
dc.identifier.volume30-
dc.identifier.issue8-
dc.identifier.spage1049-
dc.identifier.epage1055-
dc.publisher.placeUnited Kingdom-

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