{"title":"从微阵列数据中发现延迟基因调控模式","authors":"Huang-Cheng Kuo, Pei-Cheng Tsai, Jen-peng Huang","doi":"10.1109/HIS.2009.31","DOIUrl":null,"url":null,"abstract":"Discovered gene regulation networks are very helpful to predict unknown gene functions. Microarray gene expression data reveals activation and deactivation relations among genes. There are evidences showing that multiple time units delay exist in a gene regulation process. Association rule mining technique is very suitable for finding regulation relations among genes. However, current association rule mining techniques can not handle temporally ordered transactions. We propose a modified association rule mining technique for efficiently discovering time-delayed regulation relationships among genes.","PeriodicalId":414085,"journal":{"name":"2009 Ninth International Conference on Hybrid Intelligent Systems","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Finding Time-Delayed Gene Regulation Patterns from Microarray Data\",\"authors\":\"Huang-Cheng Kuo, Pei-Cheng Tsai, Jen-peng Huang\",\"doi\":\"10.1109/HIS.2009.31\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Discovered gene regulation networks are very helpful to predict unknown gene functions. Microarray gene expression data reveals activation and deactivation relations among genes. There are evidences showing that multiple time units delay exist in a gene regulation process. Association rule mining technique is very suitable for finding regulation relations among genes. However, current association rule mining techniques can not handle temporally ordered transactions. We propose a modified association rule mining technique for efficiently discovering time-delayed regulation relationships among genes.\",\"PeriodicalId\":414085,\"journal\":{\"name\":\"2009 Ninth International Conference on Hybrid Intelligent Systems\",\"volume\":\"57 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Ninth International Conference on Hybrid Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HIS.2009.31\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Ninth International Conference on Hybrid Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HIS.2009.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Finding Time-Delayed Gene Regulation Patterns from Microarray Data
Discovered gene regulation networks are very helpful to predict unknown gene functions. Microarray gene expression data reveals activation and deactivation relations among genes. There are evidences showing that multiple time units delay exist in a gene regulation process. Association rule mining technique is very suitable for finding regulation relations among genes. However, current association rule mining techniques can not handle temporally ordered transactions. We propose a modified association rule mining technique for efficiently discovering time-delayed regulation relationships among genes.