• DocumentCode
    2113256
  • Title

    Classification and Recognition of Rossmann-Fold Protein

  • Author

    Liu, Yue ; Li, Xiaoqin ; Xu, Haisong ; Qiao, Hui

  • Author_Institution
    Sch. of Life Sci. & Biomed. Eng., Beijing Univ. of Technol., Beijing
  • fYear
    2008
  • fDate
    18-18 Dec. 2008
  • Firstpage
    78
  • Lastpage
    81
  • Abstract
    Fold recognition is an important issue in protein structure research. The Rossmann-fold protein that has typical structure is a common kind of alpha/beta protein. The training set, selected from 22 families, is constituted of 79 Rossmann-fold proteins which have less than 25% sequence identity with each other. The hierarchical clustering method according to RMSD is applied and a profile-HMM based on structure alignment is built for each cluster. Testing on 9505 proteins with less than 95% sequence identity from Astral1.65, the sensitivity, specificity and MCC are 93.9%, 82.1% and 0.876 respectively. The result shows that building profile-HMMs after classification could reach precise fold recognition while a unified one cannot be built due to there are too many members in training set.
  • Keywords
    biology computing; hidden Markov models; pattern classification; pattern clustering; proteins; sequences; RMSD; Rossmann-fold protein classification; Rossmann-fold protein recognition; hierarchical clustering method; profile-HMM; protein structure alignment; root mean square deviation; training set; Biomedical engineering; Buildings; Clustering methods; Hidden Markov models; Protein engineering; Seminars; Sequences; Spatial databases; Testing; Topology; RMSD; Rossmann-fold protein; fold recognition; hierarchical clustering; profile-HMM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Future BioMedical Information Engineering, 2008. FBIE '08. International Seminar on
  • Conference_Location
    Wuhan, Hubei
  • Print_ISBN
    978-0-7695-3561-6
  • Type

    conf

  • DOI
    10.1109/FBIE.2008.76
  • Filename
    5076690