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

Content Provider	IEEE Xplore Digital Library
Author	Hsien-Da Huang Huei-Lin Chang Tsung-Shan Tsou Baw-Jhiune Liu Cheng-Yan Kao Jorng-Tzong Horng
Copyright Year	2003
Description	Author affiliation: Dept. of Comput. Sci. & Inf. Eng., Nat. Central Univ., Chung-li, Taiwan (Hsien-Da Huang)
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 differential gene groups. The association rules mined would facilitate to predict putative regulatory elements and identify genes potentially co-regulated by the putative regulatory elements.
Sponsorship	IEEE Comput. Soc. Inf. Technol. Res. Inst. at Wright State Univ. IEEE Neural Networks Soc
Starting Page	297
Ending Page	304
File Size	300487
Page Count	8
File Format	PDF
ISBN	0769519075
DOI	10.1109/BIBE.2003.1188966
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-03-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Humans Genomics Bioinformatics Gene expression Large-scale systems Computer science Libraries Proteins Statistical analysis
Content Type	Text
Resource Type	Article

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