Hsien-Da Huang, Jorng-Tzong Horng, Yi-Ming Sun, A. Tsou, Shir-Ly Huang
{"title":"Identifying transcriptional regulatory sites in the human genome using an integrated computation","authors":"Hsien-Da Huang, Jorng-Tzong Horng, Yi-Ming Sun, A. Tsou, Shir-Ly Huang","doi":"10.1109/ISPAN.2004.1300550","DOIUrl":null,"url":null,"abstract":"Recently, biological databases and analytical methods have become available for analyzing gene expression and transcriptional regulatory sequences. However, users must make the complicated analyses to query the data in various databases, and to analyze the gene upstreams using various predictive tools. Beyond methods for predicting transcriptional regulatory sites, new automated and integrated methods for analyzing gene upstream sequences on a higher level are urgently required. We present an integrated system to predict transcriptional regulatory sites and detect co-occurrence of these regulatory sites after a set of genes are input. The system comprises a biological data warehousing system, pattern discovery programs, pattern occurrence association detectors and user interfaces. User profiles and history pages enable users to trace the sequence analyses for transcriptional regulatory sites.","PeriodicalId":198404,"journal":{"name":"7th International Symposium on Parallel Architectures, Algorithms and Networks, 2004. Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2004-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"7th International Symposium on Parallel Architectures, Algorithms and Networks, 2004. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPAN.2004.1300550","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Recently, biological databases and analytical methods have become available for analyzing gene expression and transcriptional regulatory sequences. However, users must make the complicated analyses to query the data in various databases, and to analyze the gene upstreams using various predictive tools. Beyond methods for predicting transcriptional regulatory sites, new automated and integrated methods for analyzing gene upstream sequences on a higher level are urgently required. We present an integrated system to predict transcriptional regulatory sites and detect co-occurrence of these regulatory sites after a set of genes are input. The system comprises a biological data warehousing system, pattern discovery programs, pattern occurrence association detectors and user interfaces. User profiles and history pages enable users to trace the sequence analyses for transcriptional regulatory sites.