• DocumentCode
    3047285
  • Title

    Amino Acid Composition Distribution: a Novel Sequence Representation for Prediction of Protein Subcellular Localization

  • Author

    Shi, Jianyu ; Zhang, Shaowu ; Pan, Quan ; Zhou, Guo-Ping

  • Author_Institution
    Sch. of Comput. Sci., Northwestern Polytech. Univ., Xi´´an
  • fYear
    2007
  • fDate
    6-8 July 2007
  • Firstpage
    115
  • Lastpage
    118
  • Abstract
    A novel representation of protein sequence, amino acid composition distribution (AACD), is introduced to perform prediction of subcellular localization in this paper. First, a protein sequence is divided equally into multiple segments. Then, amino acid composition of each segment is calculated in series. After that, each protein sequence can be represented a feature vector. Finally, feature vectors of all sequences are further input into multi-class support vector machines to predict the subcellular localization. The results show that AACD is more effective to represent protein sequence and is non-sensitive to sequence similarity because of the better ability to reflect the information of protein subcellular localization.
  • Keywords
    biology computing; cellular biophysics; molecular biophysics; proteins; support vector machines; amino acid composition distribution; biology computing; protein sequence; protein subcellular localization; support vector machines; Amino acids; Automation; Chemistry; Computer science; Databases; Prediction methods; Protein sequence; Sequences; Support vector machines; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, 2007. ICBBE 2007. The 1st International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    1-4244-1120-3
  • Type

    conf

  • DOI
    10.1109/ICBBE.2007.33
  • Filename
    4272517