• DocumentCode
    3458025
  • Title

    Improving prediction of drug therapy outcome via integration of time series gene expression and Protein Protein Interaction network

  • Author

    Qian, Liwei ; Zheng, Haoran

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
  • fYear
    2012
  • fDate
    18-20 Aug. 2012
  • Firstpage
    12
  • Lastpage
    16
  • Abstract
    Drug therapy to patients is often with partial success, and has been associated with a number of adverse reactions. Prediction of patients´ response to therapy at the early stage of the treatment is crucial to avoiding those unnecessary adverse reactions. In this paper, a new approach that integrates time series gene expression and Protein Protein Interaction (PPI) network is presented to improve the prediction of patients´ response to drug therapy. Experimental results showed that our method outperformed previous approaches. The method proposed here offers a huge potential for applications in pharmacogenomics and medicine.
  • Keywords
    complex networks; drugs; genetics; hidden Markov models; medical computing; patient treatment; support vector machines; time series; PPI network; drug therapy outcome prediction; medicine; patient treatment response; pharmacogenomics; protein-protein interaction network; time series gene expression; Drugs; Gene expression; Hidden Markov models; Proteins; Time series analysis; PPI network; clinical studies; gene expression; time series;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems Biology (ISB), 2012 IEEE 6th International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4673-4396-1
  • Electronic_ISBN
    978-1-4673-4397-8
  • Type

    conf

  • DOI
    10.1109/ISB.2012.6314105
  • Filename
    6314105