@inproceedings{944ff189eed04e6fad0c88afd82763bf,
title = "A data mining method to predict transcriptional regulatory sites based on differentially expressed genes in human genome",
abstract = "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.",
keywords = "Data mining, Gene expression, Regulatory site, Transcription factor",
author = "Huang, {Hsien Da} and Chang, {Huei Lin} and Tsou, {Tsung Shan} and Liu, {Baw Jhiune} and Kao, {Cheng Yan} and Horng, {Jorng Tzong}",
note = "Publisher Copyright: {\textcopyright} 2003 IEEE.; 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003 ; Conference date: 10-03-2003 Through 12-03-2003",
year = "2003",
doi = "10.1109/BIBE.2003.1188966",
language = "???core.languages.en_GB???",
series = "Proceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "297--304",
booktitle = "Proceedings - 3rd IEEE Symposium on BioInformatics and BioEngineering, BIBE 2003",
}