• DocumentCode
    926191
  • Title

    Machine learning for multimodality genomic signal processing

  • Author

    Kung, Sun-Yuan ; Mak, Man-Wai

  • Author_Institution
    Dept. of Electr. Eng., Princeton Univ., NJ, USA
  • Volume
    23
  • Issue
    3
  • fYear
    2006
  • fDate
    5/1/2006 12:00:00 AM
  • Firstpage
    117
  • Lastpage
    121
  • Abstract
    This paper discusses how machine learning can be applied to genomic signal processing, particularly via fusion of multiple biological or algorithmic modalities, to improve prediction performance.
  • Keywords
    biological techniques; genetic engineering; genetics; learning (artificial intelligence); medical signal processing; algorithmic modality fusion; machine learning; multimodality genomic signal processing; multiple biological fusion; prediction performance improvement; Bioinformatics; Biomedical signal processing; Cancer; Computational biology; Diversity reception; Feature extraction; Gene expression; Genomics; Machine learning; Signal processing;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2006.1628886
  • Filename
    1628886
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=926191