• DocumentCode
    471649
  • Title

    Robust Mixture Model Clustering of DNA Binding Sites

  • Author

    Sheng Liu ; Qing Song ; Aize Cao ; Xulei Yang ; Yilei Wu

  • fYear
    2006
  • fDate
    Aug. 30 2006-Sept. 3 2006
  • Firstpage
    2032
  • Lastpage
    2035
  • Abstract
    Nucleotide sequences contain motifs that preserved through evolution because they are important to the structure or function of the molecules. DNA binding site analysis is an important issue in biology experiments as well as in computational methods. To find DNA binding sites that bind to specific transcription factors, we develop a robust mixed effect mixture model (RMEMM). The DNA sequences are represented as mixed effect model of position specific frequency, considering the relationship of frequency between positions. The results show that the mean effect is similar to position-specific scoring matrices (PSSM), providing a new view of the sequence. This model is robust to outliers or data with a bit large tails on distribution
  • Keywords
    DNA; biochemistry; biology computing; molecular biophysics; pattern clustering; DNA binding site analysis; DNA sequences; computational methods; motifs; nucleotide sequences; position-specific scoring matrices; robust mixed effect mixture model clustering; transcription factors; Bioinformatics; Biological system modeling; Biology computing; DNA computing; Evolution (biology); Frequency; Genomics; Proteins; Robustness; Sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2006. EMBS '06. 28th Annual International Conference of the IEEE
  • Conference_Location
    New York, NY
  • ISSN
    1557-170X
  • Print_ISBN
    1-4244-0032-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2006.260414
  • Filename
    4462184