Genome-wide prediction of transcriptional regulatory elements of human promoters using gene expression and promoter analysis dat

Background: A complete understanding of the regulatory mechanisms of gene expression is the next important issue of genomics. Many bioinformaticians have developed methods and algorithms for predicting transcriptional regulatory mechanisms from sequence, gene expression, and binding data. However, most of these studies involved the use of yeast which has much simpler regulatory networks than human and has many genome wide binding data and gene expression data under diverse conditions. Studies of genome wide transcriptional networks of human genomes currently lag behind those of yeast. Results: We report herein a new method that combines gene expression data analysis with promoter analysis to infer transcriptional regulatory elements of human genes. The Z scores from the application of gene set analysis with gene sets of transcription factor binding sites (TFBSs) were successfully used to represent the activity of TFBSs in a given microarray data set. A significant correlation between ...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Seon-Young Kim, YongSung Kim
• Keywords: BMCBI 2006, Gene, Gene Expression, Transcriptional Regulatory Elements