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dc.contributor.author | Furió-Tarí, Pedro | es_ES |
dc.contributor.author | Tarazona Campos, Sonia | es_ES |
dc.contributor.author | Gabaldón, Toni | es_ES |
dc.contributor.author | Enright, Anton J. | es_ES |
dc.contributor.author | Conesa, Ana | es_ES |
dc.date.accessioned | 2017-04-27T14:57:43Z | |
dc.date.available | 2017-04-27T14:57:43Z | |
dc.date.issued | 2016-05 | |
dc.identifier.issn | 0305-1048 | |
dc.identifier.uri | http://hdl.handle.net/10251/80139 | |
dc.description | C The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. | es_ES |
dc.description.abstract | [EN] Non-coding RNA transcripts such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are important genetic regulators. However, the functions of many of these transcripts are still not clearly understood. Recently, it has become apparent that there is significant crosstalk between miRNAs and lncRNAs and that this creates competition for binding between the miRNA, a lncRNA and other regulatory targets. Indeed, various competitive endogenous RNAs (ceRNAs) have already been identified where a lncRNA acts by sequestering miRNAs. This implies the down-regulation in the interaction of the miRNAs with their mRNA targets, what has been called a sponge effect. Multiple approaches exist for the prediction of miRNA targets in mRNAs. However, few methods exist for the prediction of miRNA response elements (MREs) in lncRNAs acting as ceRNAs (sponges). Here, we present spongeScan (http://spongescan.rc.ufl.edu), a graphical web tool to compute and visualize putative MREs in lncRNAs, along with different measures to assess their likely behavior as ceRNAs. | es_ES |
dc.description.sponsorship | FP7 STATegra project [agreement number 36000]; MINECO, co-funded with European Regional Development Funds (ERDF) [BIO2012-40244]; European Molecular Biology Laboratory and the European Union and ERC Seventh Framework Programme (FP7/2007-2013) [ERC-2012-StG-310325]. Funding for open access charge: University of Florida funds. | en_EN |
dc.language | Inglés | es_ES |
dc.publisher | Oxford University Press (OUP) | es_ES |
dc.relation.ispartof | Nucleic Acids Research | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | LncRNAs | es_ES |
dc.subject | CeRNAs | es_ES |
dc.subject | MiRNAs | es_ES |
dc.subject | Sponge | es_ES |
dc.subject | MRE | es_ES |
dc.subject.classification | ESTADISTICA E INVESTIGACION OPERATIVA | es_ES |
dc.title | spongeScan: A web for detecting microRNA binding elements in lncRNA sequences | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1093/nar/gkw443 | |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//BIO2012-40244/ES/DESARROLLO DE RECURSOS COMPUTACIONALES PARA LA CARACTERIZACION Y ANOTACION FUNCIONAL DE ARN NO CODIFICANTE./ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/FP7 STATegra project/36000/EU/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/FP7/310325/EU/Evolutionary genomics of long, non-coding RNAs/ | |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Facultad de Administración y Dirección de Empresas - Facultat d'Administració i Direcció d'Empreses | es_ES |
dc.description.bibliographicCitation | Furió-Tarí, P.; Tarazona Campos, S.; Gabaldón, T.; Enright, AJ.; Conesa, A. (2016). spongeScan: A web for detecting microRNA binding elements in lncRNA sequences. Nucleic Acids Research. 44((W1)):176-180. https://doi.org/10.1093/nar/gkw443 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | http://dx.doi.org/10.1093/nar/gkw443 | es_ES |
dc.description.upvformatpinicio | 176 | es_ES |
dc.description.upvformatpfin | 180 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 44 | es_ES |
dc.description.issue | (W1) | es_ES |
dc.relation.senia | 312988 | es_ES |
dc.identifier.eissn | 1362-4962 | |
dc.identifier.pmid | 27198221 | en_EN |
dc.identifier.pmcid | PMC4987953 | en_EN |
dc.contributor.funder | Ministerio de Economía y Competitividad | |
dc.description.references | Lewis, B. P., Burge, C. B., & Bartel, D. P. (2005). Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets. Cell, 120(1), 15-20. doi:10.1016/j.cell.2004.12.035 | es_ES |
dc.description.references | Agarwal V. Bell G.W. Nam J.W. Bartel D.P. Predicting effective microRNA target sites in mammalian mRNAs. eLife 2015;4. doi:10.7554/eLife.05005. | es_ES |
dc.description.references | Enright, A. J., John, B., Gaul, U., Tuschl, T., Sander, C., & Marks, D. S. (2003). Genome Biology, 5(1), R1. doi:10.1186/gb-2003-5-1-r1 | es_ES |
dc.description.references | Krek, A., Grün, D., Poy, M. N., Wolf, R., Rosenberg, L., Epstein, E. J., … Rajewsky, N. (2005). Combinatorial microRNA target predictions. Nature Genetics, 37(5), 495-500. doi:10.1038/ng1536 | es_ES |
dc.description.references | Memczak, S., Jens, M., Elefsinioti, A., Torti, F., Krueger, J., Rybak, A., … Rajewsky, N. (2013). Circular RNAs are a large class of animal RNAs with regulatory potency. Nature, 495(7441), 333-338. doi:10.1038/nature11928 | es_ES |
dc.description.references | Paraskevopoulou, M. D., Vlachos, I. S., Karagkouni, D., Georgakilas, G., Kanellos, I., Vergoulis, T., … Hatzigeorgiou, A. G. (2015). DIANA-LncBase v2: indexing microRNA targets on non-coding transcripts. Nucleic Acids Research, 44(D1), D231-D238. doi:10.1093/nar/gkv1270 | es_ES |
dc.description.references | Li, J.-H., Liu, S., Zhou, H., Qu, L.-H., & Yang, J.-H. (2013). starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein–RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Research, 42(D1), D92-D97. doi:10.1093/nar/gkt1248 | es_ES |
dc.description.references | Cunningham, F., Amode, M. R., Barrell, D., Beal, K., Billis, K., Brent, S., … Flicek, P. (2014). Ensembl 2015. Nucleic Acids Research, 43(D1), D662-D669. doi:10.1093/nar/gku1010 | es_ES |
dc.description.references | Kozomara, A., & Griffiths-Jones, S. (2013). miRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Research, 42(D1), D68-D73. doi:10.1093/nar/gkt1181 | es_ES |
dc.description.references | Medina, I., Salavert, F., Sanchez, R., de Maria, A., Alonso, R., Escobar, P., … Dopazo, J. (2013). Genome Maps, a new generation genome browser. Nucleic Acids Research, 41(W1), W41-W46. doi:10.1093/nar/gkt530 | es_ES |
dc.description.references | ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489:57-74. | es_ES |
dc.description.references | Conesa, A., Madrigal, P., Tarazona, S., Gomez-Cabrero, D., Cervera, A., McPherson, A., … Mortazavi, A. (2016). A survey of best practices for RNA-seq data analysis. Genome Biology, 17(1). doi:10.1186/s13059-016-0881-8 | es_ES |
dc.description.references | Kim, D., Pertea, G., Trapnell, C., Pimentel, H., Kelley, R., & Salzberg, S. L. (2013). TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biology, 14(4), R36. doi:10.1186/gb-2013-14-4-r36 | es_ES |
dc.description.references | Anders, S., Pyl, P. T., & Huber, W. (2014). HTSeq--a Python framework to work with high-throughput sequencing data. Bioinformatics, 31(2), 166-169. doi:10.1093/bioinformatics/btu638 | es_ES |