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Comprehensive prediction of lncRNA–RNA interactions in human transcriptome

MOTIVATION: Recent studies have revealed that large numbers of non-coding RNAs are transcribed in humans, but only a few of them have been identified with their functions. Identification of the interaction target RNAs of the non-coding RNAs is an important step in predicting their functions. The cur...

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Detalles Bibliográficos
Autores principales: Terai, Goro, Iwakiri, Junichi, Kameda, Tomoshi, Hamada, Michiaki, Asai, Kiyoshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4895283/
https://www.ncbi.nlm.nih.gov/pubmed/26818453
http://dx.doi.org/10.1186/s12864-015-2307-5
Descripción
Sumario:MOTIVATION: Recent studies have revealed that large numbers of non-coding RNAs are transcribed in humans, but only a few of them have been identified with their functions. Identification of the interaction target RNAs of the non-coding RNAs is an important step in predicting their functions. The current experimental methods to identify RNA–RNA interactions, however, are not fast enough to apply to a whole human transcriptome. Therefore, computational predictions of RNA–RNA interactions are desirable, but this is a challenging task due to the huge computational costs involved. RESULTS: Here, we report comprehensive predictions of the interaction targets of lncRNAs in a whole human transcriptome for the first time. To achieve this, we developed an integrated pipeline for predicting RNA–RNA interactions on the K computer, which is one of the fastest super-computers in the world. Comparisons with experimentally-validated lncRNA–RNA interactions support the quality of the predictions. Additionally, we have developed a database that catalogs the predicted lncRNA–RNA interactions to provide fundamental information about the targets of lncRNAs. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-2307-5) contains supplementary material, which is available to authorized users.