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

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题名:	A data mining method to predict transcriptional regulatory sites based on differentially expressed genes in human genome
作者:	H. D. Huang;H. L. Chang;T. S. Tsou;B. J. Liu;J. T. Horng
贡献者:	Department of Bioinformatics
关键词:	regulatory site;transcription factor;data mining;gene expression;UniGene;EST
日期:	2003-11
上传时间:	2010-03-19 08:24:22 (UTC+0)
出版者:	Asia University
摘要:	Very large-scale gene expression analysis, i.e., UniGene and dbEST, is 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.
關聯:	Journal of Information Science and Engineering 19 (6): 923-942
显示于类别:	[生物資訊與醫學工程學系 ] 期刊論文

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