{"title":"基于隐向量状态模型判别训练的蛋白质-蛋白质相互作用提取","authors":"Deyu Zhou, Yulan He","doi":"10.3115/1572306.1572328","DOIUrl":null,"url":null,"abstract":"The knowledge about gene clusters and protein interactions is important for biological researchers to unveil the mechanism of life. However, large quantity of the knowledge often hides in the literature, such as journal articles, reports, books and so on. Many approaches focusing on extracting information from unstructured text, such as pattern matching, shallow and deep parsing, have been proposed especially for extracting protein-protein interactions (Zhou and He, 2008).","PeriodicalId":200974,"journal":{"name":"Workshop on Biomedical Natural Language Processing","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Extracting Protein-Protein Interaction based on Discriminative Training of the Hidden Vector State Model\",\"authors\":\"Deyu Zhou, Yulan He\",\"doi\":\"10.3115/1572306.1572328\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The knowledge about gene clusters and protein interactions is important for biological researchers to unveil the mechanism of life. However, large quantity of the knowledge often hides in the literature, such as journal articles, reports, books and so on. Many approaches focusing on extracting information from unstructured text, such as pattern matching, shallow and deep parsing, have been proposed especially for extracting protein-protein interactions (Zhou and He, 2008).\",\"PeriodicalId\":200974,\"journal\":{\"name\":\"Workshop on Biomedical Natural Language Processing\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Workshop on Biomedical Natural Language Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3115/1572306.1572328\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Biomedical Natural Language Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3115/1572306.1572328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Extracting Protein-Protein Interaction based on Discriminative Training of the Hidden Vector State Model
The knowledge about gene clusters and protein interactions is important for biological researchers to unveil the mechanism of life. However, large quantity of the knowledge often hides in the literature, such as journal articles, reports, books and so on. Many approaches focusing on extracting information from unstructured text, such as pattern matching, shallow and deep parsing, have been proposed especially for extracting protein-protein interactions (Zhou and He, 2008).