{"title":"精确DNA碱基召唤的聚类方法","authors":"E. Manolakos","doi":"10.1109/ACSSC.2002.1197197","DOIUrl":null,"url":null,"abstract":"Routinely extending the useful read-lengths of DNA chromatograms beyond 1 kps by employing intelligent base-calling algorithms will be extremely useful to genomics research because in many cases the entire coding region of a gene could fit into a single long read. By segmenting the chromatograms into base-call \"events\" to be labeled in terms of the number of bases they represent, base-calling as a pattern classification problem is formulated. An overview of two unsupervised clustering methods that could be used for its solution is presented.","PeriodicalId":284950,"journal":{"name":"Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Clustering methods for accurate DNA base-calling\",\"authors\":\"E. Manolakos\",\"doi\":\"10.1109/ACSSC.2002.1197197\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Routinely extending the useful read-lengths of DNA chromatograms beyond 1 kps by employing intelligent base-calling algorithms will be extremely useful to genomics research because in many cases the entire coding region of a gene could fit into a single long read. By segmenting the chromatograms into base-call \\\"events\\\" to be labeled in terms of the number of bases they represent, base-calling as a pattern classification problem is formulated. An overview of two unsupervised clustering methods that could be used for its solution is presented.\",\"PeriodicalId\":284950,\"journal\":{\"name\":\"Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002.\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.2002.1197197\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.2002.1197197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Routinely extending the useful read-lengths of DNA chromatograms beyond 1 kps by employing intelligent base-calling algorithms will be extremely useful to genomics research because in many cases the entire coding region of a gene could fit into a single long read. By segmenting the chromatograms into base-call "events" to be labeled in terms of the number of bases they represent, base-calling as a pattern classification problem is formulated. An overview of two unsupervised clustering methods that could be used for its solution is presented.