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MeInfoText: associated gene methylation and cancer information from text mining

Yu-Ching Fang1, Hsuan-Cheng Huang2* and Hsueh-Fen Juan1345*

Author Affiliations

1 Institute of Molecular and Cellular Biology, National Taiwan University, Taipei 106, Taiwan

2 Institute of Biomedical Informatics, National Yang-Ming University, Taipei 112, Taiwan

3 Department of Life Science, National Taiwan University, Taipei 106, Taiwan

4 Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 106, Taiwan

5 Center for Systems Biology and Bioinformatics, National Taiwan University, Taipei 106, Taiwan

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BMC Bioinformatics 2008, 9:22  doi:10.1186/1471-2105-9-22

Published: 14 January 2008



DNA methylation is an important epigenetic modification of the genome. Abnormal DNA methylation may result in silencing of tumor suppressor genes and is common in a variety of human cancer cells. As more epigenetics research is published electronically, it is desirable to extract relevant information from biological literature. To facilitate epigenetics research, we have developed a database called MeInfoText to provide gene methylation information from text mining.


MeInfoText presents comprehensive association information about gene methylation and cancer, the profile of gene methylation among human cancer types and the gene methylation profile of a specific cancer type, based on association mining from large amounts of literature. In addition, MeInfoText offers integrated protein-protein interaction and biological pathway information collected from the Internet. MeInfoText also provides pathway cluster information regarding to a set of genes which may contribute the development of cancer due to aberrant methylation. The extracted evidence with highlighted keywords and the gene names identified from each methylation-related abstract is also retrieved. The database is now available at webcite.


MeInfoText is a unique database that provides comprehensive gene methylation and cancer association information. It will complement existing DNA methylation information and will be useful in epigenetics research and the prevention of cancer.