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dc.contributor.authorYang, Yuedong
dc.contributor.authorZhao, Huiying
dc.contributor.authorWang, Jihua
dc.contributor.authorZhou, Yaoqi
dc.contributor.editorKihara, D
dc.date.accessioned2019-04-03T23:34:43Z
dc.date.available2019-04-03T23:34:43Z
dc.date.issued2014
dc.identifier.isbn978-1-4939-0365-8
dc.identifier.doi10.1007/978-1-4939-0366-5_9
dc.identifier.urihttp://hdl.handle.net/10072/66241
dc.description.abstractRNA-binding proteins (RBPs) play key roles in RNA metabolism and post-transcriptional regulation. Computational methods have been developed separately for prediction of RBPs and RNA-binding residues by machine-learning techniques and prediction of protein-RNA complex structures by rigid or semiflexible structure-to-structure docking. Here, we describe a template-based technique called SPOT-Seq-RNA that integrates prediction of RBPs, RNA-binding residues, and protein-RNA complex structures into a single package. This integration is achieved by combining template-based structure-prediction software, SPARKS X, with binding affinity prediction software, DRNA. This tool yields reasonable sensitivity (46 %) and high precision (84 %) for an independent test set of 215 RBPs and 5,766 non-RBPs. SPOT-Seq-RNA is computationally efficient for genome-scale prediction of RBPs and protein-RNA complex structures. Its application to human genome study has revealed a similar sensitivity and ability to uncover hundreds of novel RBPs beyond simple homology.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.languageEnglish
dc.publisherSpringer
dc.publisher.placeUnited States
dc.publisher.urihttp://dx.doi.org/10.1007/978-1-4939-0366-5
dc.relation.ispartofbooktitleMethods in Molecular Biology
dc.relation.ispartofchapter9
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom119
dc.relation.ispartofpageto130
dc.relation.ispartofedition3rd
dc.rights.retentionY
dc.subject.fieldofresearchBiological Sciences not elsewhere classified
dc.subject.fieldofresearchBiochemistry and Cell Biology
dc.subject.fieldofresearchOther Chemical Sciences
dc.subject.fieldofresearchcode069999
dc.subject.fieldofresearchcode0601
dc.subject.fieldofresearchcode0399
dc.titleSPOT-Seq-RNA: Predicting Protein–RNA Complex Structure and RNA-Binding Function by Fold Recognition and Binding Affinity Prediction
dc.typeBook chapter
dc.type.descriptionB1 - Chapters
dc.type.codeB - Book Chapters
dc.description.versionPost-print
gro.facultyOffice of the Snr Dep Vice Chancellor, Institute for Glycomics
gro.rights.copyright© 2014 Springer. This is the author-manuscript version of this paper. It is reproduced here in accordance with the copyright policy of the publisher. Please refer to the publisher’s website for further information.
gro.hasfulltextFull Text
gro.griffith.authorZhou, Yaoqi
gro.griffith.authorYang, Yuedong


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