Predicting methylation status of CpG islands in the human brain

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 ...

• Type: Journal
• Year: 2006
• Where: BIOINFORMATICS
• Authors: Fang Fang, Shicai Fan, Xuegong Zhang, Michael Q. Zhang
• Keywords: BIOINFORMATICS 2006, CpG Islands, DNA Methylation, Methylation