Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81687
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dc.contributorDepartment of Computing-
dc.creatorWong, L-
dc.creatorHuang, YA-
dc.creatorYou, ZH-
dc.creatorChen, ZH-
dc.creatorCao, MY-
dc.date.accessioned2020-02-10T12:28:38Z-
dc.date.available2020-02-10T12:28:38Z-
dc.identifier.issn1582-1838-
dc.identifier.urihttp://hdl.handle.net/10397/81687-
dc.language.isoenen_US
dc.publisherWiley-Blackwellen_US
dc.rightsThis is an open access article under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.en_US
dc.rights© 2019 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.en_US
dc.rightsThe following publication Wong, L., Huang, Y. A., You, Z. H., Chen, Z. H., & Cao, M. Y. (2019). LNRLMI : linear neighbour representation for predicting lncRNA-miRNA interactions. Journal of Cellular and Molecular Medicine, 1-9 is available at https://dx.doi.org/10.1111/jcmm.14583en_US
dc.subjectCeRNA networken_US
dc.subjectExpression profileen_US
dc.subjectLink predictionen_US
dc.subjectLncRNA-miRNA interactionen_US
dc.titleLNRLMI : linear neighbour representation for predicting lncRNA-miRNA interactionsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1-
dc.identifier.epage9-
dc.identifier.doi10.1111/jcmm.14583-
dcterms.abstractLncRNA and miRNA are key molecules in mechanism of competing endogenous RNAs(ceRNA), and their interactions have been discovered with important roles in gene regulation. As supplementary to the identification of lncRNA-miRNA interactions from CLIP-seq experiments, in silico prediction can select the most potential candidates for experimental validation. Although developing computational tool for predicting lncRNA-miRNA interaction is of great importance for deciphering the ceRNA mechanism, little effort has been made towards this direction. In this paper, we propose an approach based on linear neighbour representation to predict lncRNA-miRNA interactions (LNRLMI). Specifically, we first constructed a bipartite network by combining the known interaction network and similarities based on expression profiles of lncRNAs and miRNAs. Based on such a data integration, linear neighbour representation method was introduced to construct a prediction model. To evaluate the prediction performance of the proposed model, k-fold cross validations were implemented. As a result, LNRLMI yielded the average AUCs of 0.8475 +/- 0.0032, 0.8960 +/- 0.0015 and 0.9069 +/- 0.0014 on 2-fold, 5-fold and 10-fold cross validation, respectively. A series of comparison experiments with other methods were also conducted, and the results showed that our method was feasible and effective to predict lncRNA-miRNA interactions via a combination of different types of useful side information. It is anticipated that LNRLMI could be a useful tool for predicting non-coding RNA regulation network that lncRNA and miRNA are involved in.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationJournal of cellular and molecular medicine, 2019, p. 1-9-
dcterms.isPartOfJournal of cellular and molecular medicine-
dcterms.issued2019-
dc.identifier.isiWOS:000488569000001-
dc.identifier.scopus2-s2.0-85073978328-
dc.identifier.eissn1582-4934-
dc.description.validate202002 bcrc-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.pubStatusPublisheden_US
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