{"title":"一种实用的基因相互作用信息提取策略。","authors":"D Proux, F Rechenmann, L Julliard","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>We present in this paper a pragmatic strategy to perform information extraction from biologic texts. Since the emergence of the information extraction field, techniques have evolved, become more robust and proved their efficiency on specific domains. We are using a combination of existing linguistic and knowledge processing tools to automatically extract information about gene interactions in the literature. Our ultimate goal is to build a network of gene interactions. The methodologies used and the current results are discussed in this paper.</p>","PeriodicalId":79420,"journal":{"name":"Proceedings. International Conference on Intelligent Systems for Molecular Biology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2000-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A pragmatic information extraction strategy for gathering data on genetic interactions.\",\"authors\":\"D Proux, F Rechenmann, L Julliard\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>We present in this paper a pragmatic strategy to perform information extraction from biologic texts. Since the emergence of the information extraction field, techniques have evolved, become more robust and proved their efficiency on specific domains. We are using a combination of existing linguistic and knowledge processing tools to automatically extract information about gene interactions in the literature. Our ultimate goal is to build a network of gene interactions. The methodologies used and the current results are discussed in this paper.</p>\",\"PeriodicalId\":79420,\"journal\":{\"name\":\"Proceedings. International Conference on Intelligent Systems for Molecular Biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. International Conference on Intelligent Systems for Molecular Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. International Conference on Intelligent Systems for Molecular Biology","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A pragmatic information extraction strategy for gathering data on genetic interactions.
We present in this paper a pragmatic strategy to perform information extraction from biologic texts. Since the emergence of the information extraction field, techniques have evolved, become more robust and proved their efficiency on specific domains. We are using a combination of existing linguistic and knowledge processing tools to automatically extract information about gene interactions in the literature. Our ultimate goal is to build a network of gene interactions. The methodologies used and the current results are discussed in this paper.