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Bioinformatics Advance Access published online on July 12, 2006
Bioinformatics, doi:10.1093/bioinformatics/btl377
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© The Author (2006). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org
Received May 29, 2006
Revised June 24, 2006
Accepted July 5, 2006

Article

Predicting methylation status of CpG islands in the human brain

Fang Fang 1, Shicai Fan 1, Xuegong Zhang 1, and Michael Q. Zhang 2 *

1 Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, 100084 China
2 Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11274, USA; Bioinformatics Division, TNLIST, Department of Automation, Tsinghua University, 100084 China

* To whom correspondence should be addressed.
Michael Q. Zhang, E-mail: mzhang{at}cshl.edu


  Abstract

Motivation: Over 50% of human genes contain CpG islands in their 5'-regions. Methylation patterns of CpG islands are involved in tissue-specific gene expression and regulation. Mis-epigenetic silencing associated with aberrant CpG island methylation is one mechanism leading to the loss of tumor suppressor functions in cancer cells. Large-scale experimental detection of DNA methylation is still both labor-intensive and time-consuming. Therefore, it is necessary to develop in silico approaches for predicting methylation status of CpG islands.

Results: Based on a recent genome-scale dataset of DNA methylation in human brain tissues, we developed a classifier called MethCGI for predicting methylation status of CpG islands using a Support Vector Machine (SVM). Nucleotide sequence contents as well as Transcription Factor Binding Sites (TFBSs) are used as features for the classification. The method achieves specificity of 84.65% and sensitivity of 84.32% on the brain data, and can also correctly predict about 2/3 of the data from other tissues reported in the MethDB database.

Availability: An online predictor based on MethCGI is available at http://166.111.201.7/MethCGI.html.

Supplementary: http://166.111.201.7/help.html.

Associate Editor: Keith A Crandall
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