• DocumentCode
    1654210
  • Title

    Using Grey Model GM(2,1) and Pseudo Amino Acid Composition to Predict Protein Subcellular Location

  • Author

    Lin, Wei-Zhong ; Xiao, Xuan

  • Author_Institution
    Sch. of Inf. Eng., Jing-De-Zhen Ceramic Inst., Jingdezhen
  • fYear
    2008
  • Firstpage
    718
  • Lastpage
    721
  • Abstract
    Identifying the subcellular localization of proteins is particularly helpful in the functional annotation of gene products. Based on the concept of pseudo amino acid composition, a novel representation of protein sequence, grey pseudo amino acid (grey-PseAA) was introduced. The advantage by incorporating the grey-PseAA into the pseudo amino acid composition is that it can catch the essence of the overall sequence pattern of a protein and hence more effectively reflect its sequence-order effects. It was demonstrated thru the jackknife cross validation test and independent dataset test that the overall success rates by the new approach were significantly improved. It is anticipated that the concept of grey-PseAA composition can be also used to predict many other protein attributes, such as membrane protein type, enzyme functional class, GPCR type, protease type, among many others.
  • Keywords
    cellular biophysics; genetics; molecular biophysics; proteins; GPCR type; enzyme functional class; gene product functional annotation; gene product representation; grey model GM(2,1); grey pseudoamino acid; grey-PseAA; independent dataset test; jackknife cross validation test; membrane protein type; protease type; protein sequence pattern; protein subcellular location prediction; pseudoamino acid composition; sequence order effects; subcellular protein localization; Amino acids; Biochemistry; Biomembranes; Ceramics; Electron microscopy; Prediction algorithms; Predictive models; Protein engineering; Protein sequence; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1747-6
  • Electronic_ISBN
    978-1-4244-1748-3
  • Type

    conf

  • DOI
    10.1109/ICBBE.2008.175
  • Filename
    4535055