MeInfoText: associated gene methylation and cancer information from text mining

By Yu-Ching Fang, Hsuan-Cheng Huang, Hsueh‐Fen Juan. 2008

43 citations recorded by the source corpus.

BackgroundDNA 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.DescriptionMeInfoText 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 http://mit.lifescience.ntu.edu.tw/.ConclusionMeInfoText 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.

Subfields: Molecular Biology

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In Molecular Biology

1. Zexian Zeng
2. Tristan Naumann
3. Xiaoyu Li
4. Yu Deng
5. Yuan Luo

Citations in the corpus

• Natural Language Processing for EHR-Based Computational Phenotyping (2018, background): “In addition to hospital-collected data stored in EHRs, research data are increasingly available, including public databases such as PubMed [17], Textpresso [18], Human Protein Interaction Database (HPID) [19], and MeInfoText [20].”
• Biomedical text mining and its applications in cancer research (2013, unknown): “[79] Fang YC, Huang HC, Juan HF. MeInfoText: associated gene methylation and cancer information from text mining.”