• DocumentCode
    2413664
  • Title

    Correlating CpG islands, motifs, and sequence variants in human chromosome 21

  • Author

    Spontaneo, Leah ; Cercone, Nick

  • Author_Institution
    Dept. of Comput. Sci. & Eng., York Univ., Toronto, ON, Canada
  • fYear
    2010
  • fDate
    18-21 Dec. 2010
  • Firstpage
    319
  • Lastpage
    322
  • Abstract
    CpG islands are important regions in DNA. They usually appear at the 5´ end of genes containing GC-rich dinucleotides. When DNA methylation occurs, gene regulation is affected and it sometimes leads to carcinogenesis. We propose a new detection program using a hidden Markov model alongside the Viterbi algorithm. Our solution provides a graphical user interface not seen in many of the other CGI detection programs and we unify the detection and analysis under one program to allow researchers to scan a genetic sequence, detect the significant CGIs, and analyze the sequence once the scan is complete for any noteworthy findings. Using human chromosome 21, we run an analysis on a dataset of promoters and discover that the characteristics of methylated and unmethylated CGIs are significantly different. Finally, we detected significantly different motifs between methylated and unmethylated CGI promoters using MEME and MAST.
  • Keywords
    DNA; biology computing; cancer; dynamic programming; genetics; graphical user interfaces; hidden Markov models; molecular biophysics; molecular configurations; pattern recognition; CGI detection programs; CpG island correlation; DNA methylation; GC-rich dinucleotides; MAST; MEME; Viterbi algorithm; carcinogenesis; gene regulation; genetic sequence scanning; graphical user interface; hidden Markov model; human chromosome 21; methylated CGI characteristics; motif correlation; sequence variant correlation; Bioinformatics; Cancer; DNA; Genomics; Hidden Markov models; Humans;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedicine (BIBM), 2010 IEEE International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-8306-8
  • Electronic_ISBN
    978-1-4244-8307-5
  • Type

    conf

  • DOI
    10.1109/BIBM.2010.5706584
  • Filename
    5706584