• DocumentCode
    1650613
  • Title

    Differential Performance Between Structural and Functional B-Cell Epitopic Residue Prediction

  • Author

    Huang, Jian ; You, Zili

  • Author_Institution
    Sch. of Life Sci. & Technol., Univ. of Electron. Sci. & Technol. of China, Chengdu
  • fYear
    2008
  • Firstpage
    93
  • Lastpage
    96
  • Abstract
    We compared the performance between the structural and functional B-cell epitope data set with sequence profiling method based on three propensity scales. One of the scales is called relative connectivity, which is newly derived from the topological parameters of residue networks. The other two are Parker´s hydrophilicity and Levitt´s index, known as the best indices so far for B-cell epitope prediction. Among all the scales and data sets tested, the best performance is always achieved with the relative connectivity, suggesting it might be the best scale for both structural and functional B-cell epitopic residue prediction. Furthermore, all the scales perform better on the structural rather than functional data sets. This indicates that these scales based sequence profiling prediction might be more appropriate for the structural B-cell epitopic residue prediction. Besides, we found that the different performance between data sets is not related to the epitopic residue density of the data set.
  • Keywords
    biological techniques; cellular biophysics; Levitt´s index; Parker´s hydrophilicity; epitopic residue density; functional B-cell epitopic residue prediction; propensity scales; relative connectivity; sequence profiling method; structural B-cell epitope data; topological parameters; Amino acids; Databases; Hidden Markov models; Neural networks; Peptides; Proteins; Sequences; Support vector machines; Testing; X-ray diffraction;
  • 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.2008.29
  • Filename
    4534909