Comprehensive prediction of lncRNA-RNA interactions in human transcriptome

Goro Terai, Junichi Iwakiri, Tomoshi Kameda, Michiaki Hamada, Kiyoshi Asai

    Research output: Contribution to journalArticle

    32 Citations (Scopus)


    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.

    Original languageEnglish
    Article number12
    JournalBMC Genomics
    Issue number1
    Publication statusPublished - 2016 Jan 11


    • 1/2-sbsRNA
    • Interaction energy
    • RNA-RNA interactions
    • TINCR

    ASJC Scopus subject areas

    • Biotechnology
    • Genetics

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