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To reduce the amount of manual curation and improve the accuracy of relation extraction, we have now developed MeInfoText 2.0, which uses a machine learning-based approach to extract gene methylation-cancer relations.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Description<\/jats:title>\n            <jats:p>Two maximum entropy models are trained to predict if aberrant gene methylation is related to any type of cancer mentioned in the literature. After evaluation based on 10-fold cross-validation, the average precision\/recall rates of the two models are 94.7\/90.1 and 91.8\/90% respectively. MeInfoText 2.0 provides the gene methylation profiles of different types of human cancer. The extracted relations with maximum probability, evidence sentences, and specific gene information are also retrievable. The database is available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/bws.iis.sinica.edu.tw:8081\/MeInfoText2\/\" ext-link-type=\"uri\">http:\/\/bws.iis.sinica.edu.tw:8081\/MeInfoText2\/<\/jats:ext-link>.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>The previous version, MeInfoText, was developed by using association rules, whereas MeInfoText 2.0 is based on a new framework that combines machine learning, dictionary lookup and pattern matching for epigenetics information extraction. The results of experiments show that MeInfoText 2.0 outperforms existing tools in many respects. To the best of our knowledge, this is the first study that uses a hybrid approach to extract gene methylation-cancer relations. It is also the first attempt to develop a gene methylation and cancer relation corpus.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-12-471","type":"journal-article","created":{"date-parts":[[2011,12,14]],"date-time":"2011-12-14T19:20:21Z","timestamp":1323890421000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":24,"title":["MeInfoText 2.0: gene methylation and cancer relation extraction from biomedical literature"],"prefix":"10.1186","volume":"12","author":[{"given":"Yu-Ching","family":"Fang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Po-Ting","family":"Lai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hong-Jie","family":"Dai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wen-Lian","family":"Hsu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2011,12,14]]},"reference":[{"issue":"13","key":"4998_CR1","doi-asserted-by":"publisher","first-page":"131","DOI":"10.1016\/j.ejphar.2009.10.011","volume":"625","author":"LS Kristensen","year":"2009","unstructured":"Kristensen LS, Nielsen HM, Hansen LL: Epigenetics and cancer treatment. 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