• DocumentCode
    3542741
  • Title

    Computational prediction of microRNA regulatory pathways

  • Author

    Yue, Dong ; Chen, Yidong ; Gao, Shou-Jiang ; Huang, Yufei

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Texas at San Antonio, San Antonio, TX, USA
  • fYear
    2011
  • fDate
    4-6 Dec. 2011
  • Firstpage
    158
  • Lastpage
    161
  • Abstract
    MicroRNAs (miRNAs) are known to regulate transcription and/or protein translation of hundreds of genes. Despite their importance, the functions of most human miRNAs are still poorly understood. In this paper, we proposed a SVM based algorithm - PathMicrO that elucidates the miRNA function by predicting the miRNA regulated pathways. PathMicrO combines the sequence-level target predictions with the gene expression profiling from the miRNA transfection experiments. The performance of PathMicrO is evaluated with cross-validation using a careful constructed training data and two independent testing data. Compared to other prediction algorithms, PathMicrO attains 77% more in sensitivity when false positive rate is equal to 0.21 and achieves much larger area under the receiver operating characteristic (ROC) curve.
  • Keywords
    RNA; biology computing; proteins; support vector machines; PathMicrO; SVM based algorithm; computational prediction; cross-validation; gene expression profiling; gene protein translation; genes transcription regulation; independent testing data; miRNA transfection experiments; microRNA regulatory pathways; receiver operating characteristic curve; sequence-level target predictions; training data; Bioinformatics; Databases; Feature extraction; Gene expression; Histograms; Prediction algorithms; Training data; PathmicrO; SVM; function; microRNA; pathway;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Genomic Signal Processing and Statistics (GENSIPS), 2011 IEEE International Workshop on
  • Conference_Location
    San Antonio, TX
  • ISSN
    2150-3001
  • Print_ISBN
    978-1-4673-0491-7
  • Electronic_ISBN
    2150-3001
  • Type

    conf

  • DOI
    10.1109/GENSiPS.2011.6169469
  • Filename
    6169469