{"title":"利用EST数据检测差异表达基因的经验贝叶斯方法。","authors":"Na You, Junmei Liu, Chang Xuan Mao","doi":"10.1155/2008/817210","DOIUrl":null,"url":null,"abstract":"<p><p>Detection of differentially expressed genes from expressed sequence tags (ESTs) data has received much attention. An empirical Bayesian method is introduced in which gene expression patterns are estimated and used to define detection statistics. Significantly differentially expressed genes can be declared given detection statistics. Simulation is done to evaluate the performance of proposed method. Two real applications are studied.</p>","PeriodicalId":73471,"journal":{"name":"International journal of plant genomics","volume":" ","pages":"817210"},"PeriodicalIF":0.0000,"publicationDate":"2008-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2008/817210","citationCount":"2","resultStr":"{\"title\":\"An empirical bayesian method for detecting differentially expressed genes using EST data.\",\"authors\":\"Na You, Junmei Liu, Chang Xuan Mao\",\"doi\":\"10.1155/2008/817210\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Detection of differentially expressed genes from expressed sequence tags (ESTs) data has received much attention. An empirical Bayesian method is introduced in which gene expression patterns are estimated and used to define detection statistics. Significantly differentially expressed genes can be declared given detection statistics. Simulation is done to evaluate the performance of proposed method. Two real applications are studied.</p>\",\"PeriodicalId\":73471,\"journal\":{\"name\":\"International journal of plant genomics\",\"volume\":\" \",\"pages\":\"817210\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1155/2008/817210\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of plant genomics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/2008/817210\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of plant genomics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2008/817210","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An empirical bayesian method for detecting differentially expressed genes using EST data.
Detection of differentially expressed genes from expressed sequence tags (ESTs) data has received much attention. An empirical Bayesian method is introduced in which gene expression patterns are estimated and used to define detection statistics. Significantly differentially expressed genes can be declared given detection statistics. Simulation is done to evaluate the performance of proposed method. Two real applications are studied.
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