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A data mining method to predict transcriptional regulatory sites based on differentially expressed genes in human genome

研究成果: 書貢獻/報告類型會議論文篇章同行評審

4 引文 斯高帕斯(Scopus)

摘要

Very large-scale gene expression analysis, i.e., UniGene and dbEST, are provided to find those genes with significantly differential expression in specific tissues. The differentially expressed genes in a specific tissue are potentially regulated concurrently by a combination of transcription factors. This study attempts to mine putative binding sites on how combinations of the known regulatory sites homologs and over-represented repetitive elements are distributed in the promoter regions of considered groups of differentially expressed genes. We propose a data mining approach to statistically discover the significantly tissue-specific combinations of known site homologs and over-represented repetitive sequences, which are distributed in the promoter regions of differentially gene groups. The association rules mined would facilitate to predict putative regulatory elements and identify genes potentially co-regulated by the putative regulatory elements.

原文???core.languages.en_GB???
主出版物標題Proceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003
發行者Institute of Electrical and Electronics Engineers Inc.
頁面297-304
頁數8
ISBN(電子)0769519075, 9780769519074
DOIs
出版狀態已出版 - 2003
事件3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003 - Bethesda, United States
持續時間: 10 3月 200312 3月 2003

出版系列

名字Proceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003

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???event.eventtypes.event.conference???3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003
國家/地區United States
城市Bethesda
期間10/03/0312/03/03

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