• DocumentCode
    191022
  • Title

    Identification of protein interaction methods from biomedical literature

  • Author

    Jhamb, Deepali ; Krishnan, Arjun ; Palakal, Mathew ; Pandit, Yogesh ; Palakal, Mathew J. ; Duraiswamy, Premkumar

  • Author_Institution
    Sch. of Inf. & Comput., Indiana Univ. - Purdue Univ., Indianapolis, IN, USA
  • fYear
    2014
  • fDate
    2-4 June 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Proteins are the functional subunits of a cell which interact with each other to carry out biological processes. Protein interaction networks form the backbone of the research in molecular and systems biology. Although there are available methods to mine protein interactions and their detection methods from the biological literature, the accuracy of these methods is quite low. In this study, we applied regular expressions to identify the three most frequent protein interaction detection methods from the methodology section of the full text articles. These articles were then further used to extract the protein protein interactions. We report an overall specificity of 83.6 and sensitivity of 78.2 for the identification of interaction methods.
  • Keywords
    biology computing; cellular biophysics; data mining; molecular biophysics; proteins; text analysis; biological processes; biomedical literature; cellular biophysics; data mining; functional subunits; molecular systems; protein-protein interaction detection methods; regular expressions; text analysis; Accuracy; Databases; Manuals; Protein engineering; Proteins; Support vector machines; data mining; protein interaction; protein interaction detection method; regex;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Advances in Bio and Medical Sciences (ICCABS), 2014 IEEE 4th International Conference on
  • Conference_Location
    Miami, FL
  • Print_ISBN
    978-1-4799-5786-6
  • Type

    conf

  • DOI
    10.1109/ICCABS.2014.6863923
  • Filename
    6863923