An improved distance measure between the expression profiles linking co-expression and co-regulation in mouse

Background: Many statistical algorithms combine microarray expression data and genome sequence data to identify transcription factor binding motifs in the low eukaryotic genomes. Finding cis-regulatory elements in higher eukaryote genomes, however, remains a challenge, as searching in the promoter regions of genes with similar expression patterns often fails. The difficulty is partially attributable to the poor performance of the similarity measures for comparing expression profiles. The widely accepted measures are inadequate for distinguishing genes transcribed from distinct regulatory mechanisms in the complicated genomes of higher eukaryotes. Results: By defining the regulatory similarity between a gene pair as the number of common known transcription factor binding motifs in the promoter regions, we compared the performance of several expression distance measures on seven mouse expression data sets. We propose a new distance measure that accounts for both the linear trends and fo...

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Ryung S. Kim, Hongkai Ji, Wing Hung Wong
• Keywords: BMCBI 2006, Expression Data, Genomes, Microarray Expression Data