{"title":"用随机方法识别启动子","authors":"T. Jabid, F. Anwar, S. M. Baker, M. Shoyaib","doi":"10.1109/ICCITECHN.2007.4579366","DOIUrl":null,"url":null,"abstract":"Analysis of a gene sequence, which is transcribed into RNA and then translated into protein, is a difficult task. If this could be achieved, it would make possible better understand how the organisms are developed from DNA information. The behavior of gene is highly influenced by promoter sequences residing upstream or downstream of the Transcription Start Site (TSS). The promoter recognition process is a part of the complex process where genes interact with each other over time and actually regulates the whole working process of a cell. This paper attempts to develop an efficient algorithm that can successfully distinguish promoters and non promoters by analyzing statistical data. A learning model is developed from the known dataset to predict the unknown ones.","PeriodicalId":338170,"journal":{"name":"2007 10th international conference on computer and information technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Identification of promoter through stochastic approach\",\"authors\":\"T. Jabid, F. Anwar, S. M. Baker, M. Shoyaib\",\"doi\":\"10.1109/ICCITECHN.2007.4579366\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analysis of a gene sequence, which is transcribed into RNA and then translated into protein, is a difficult task. If this could be achieved, it would make possible better understand how the organisms are developed from DNA information. The behavior of gene is highly influenced by promoter sequences residing upstream or downstream of the Transcription Start Site (TSS). The promoter recognition process is a part of the complex process where genes interact with each other over time and actually regulates the whole working process of a cell. This paper attempts to develop an efficient algorithm that can successfully distinguish promoters and non promoters by analyzing statistical data. A learning model is developed from the known dataset to predict the unknown ones.\",\"PeriodicalId\":338170,\"journal\":{\"name\":\"2007 10th international conference on computer and information technology\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 10th international conference on computer and information technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCITECHN.2007.4579366\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 10th international conference on computer and information technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCITECHN.2007.4579366","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Identification of promoter through stochastic approach
Analysis of a gene sequence, which is transcribed into RNA and then translated into protein, is a difficult task. If this could be achieved, it would make possible better understand how the organisms are developed from DNA information. The behavior of gene is highly influenced by promoter sequences residing upstream or downstream of the Transcription Start Site (TSS). The promoter recognition process is a part of the complex process where genes interact with each other over time and actually regulates the whole working process of a cell. This paper attempts to develop an efficient algorithm that can successfully distinguish promoters and non promoters by analyzing statistical data. A learning model is developed from the known dataset to predict the unknown ones.