{"title":"从PubMed中挖掘疾病相关的生物标志物网络","authors":"Zhong Huang","doi":"10.1109/ISB.2013.6623786","DOIUrl":null,"url":null,"abstract":"Disease related biomarker discovery is the critical step to realize the future personalized medicine and has been an important research area. With exponential growing of biomedical knowledge deposited in PubMed database, it is now an essential step to mine PubMed for biomarker-disease associations to support the laboratory research and clinical validation. We constructed list of human diseases that are most frequently associated with biomarker in literatures by text mining. Top ranked neurology diseases were then used to extract associated genes from PubMed using context sensitive information retrieval methods. Associated genes were then integrated into pathways and subject to network biomarker analysis. Our approach identifies both known and potential biomarkers for 3 neurodegenerative diseases.","PeriodicalId":151775,"journal":{"name":"2013 7th International Conference on Systems Biology (ISB)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Mining disease associated biomarker networks from PubMed\",\"authors\":\"Zhong Huang\",\"doi\":\"10.1109/ISB.2013.6623786\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Disease related biomarker discovery is the critical step to realize the future personalized medicine and has been an important research area. With exponential growing of biomedical knowledge deposited in PubMed database, it is now an essential step to mine PubMed for biomarker-disease associations to support the laboratory research and clinical validation. We constructed list of human diseases that are most frequently associated with biomarker in literatures by text mining. Top ranked neurology diseases were then used to extract associated genes from PubMed using context sensitive information retrieval methods. Associated genes were then integrated into pathways and subject to network biomarker analysis. Our approach identifies both known and potential biomarkers for 3 neurodegenerative diseases.\",\"PeriodicalId\":151775,\"journal\":{\"name\":\"2013 7th International Conference on Systems Biology (ISB)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 7th International Conference on Systems Biology (ISB)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISB.2013.6623786\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 7th International Conference on Systems Biology (ISB)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISB.2013.6623786","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Mining disease associated biomarker networks from PubMed
Disease related biomarker discovery is the critical step to realize the future personalized medicine and has been an important research area. With exponential growing of biomedical knowledge deposited in PubMed database, it is now an essential step to mine PubMed for biomarker-disease associations to support the laboratory research and clinical validation. We constructed list of human diseases that are most frequently associated with biomarker in literatures by text mining. Top ranked neurology diseases were then used to extract associated genes from PubMed using context sensitive information retrieval methods. Associated genes were then integrated into pathways and subject to network biomarker analysis. Our approach identifies both known and potential biomarkers for 3 neurodegenerative diseases.
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