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

Ryung S. Kim, Hongkai Ji, Wing H. Wong

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

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 fold-changes of expression across the samples. Conclusion: The study reveals that the proposed distance measure for comparing expression profiles enables us to identify genes with large number of common regulatory elements because it reflects the inherent regulatory information better than widely accepted distance measures such as the Pearson's correlation or cosine correlation with or without log transformation.

Original languageEnglish (US)
Article number44
JournalBMC Bioinformatics
Volume7
DOIs
StatePublished - Jan 26 2006
Externally publishedYes

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Distance Measure
Linking
Mouse
Genes
Genome
Eukaryota
Genetic Promoter Regions
Transcription Factors
Gene
Transcription factors
Transcription Factor
Promoter
Linear Trend
Pearson Correlation
Common factor
Profile
Similarity Measure
Microarray
Microarrays
Fold

ASJC Scopus subject areas

  • Medicine(all)
  • Structural Biology
  • Applied Mathematics

Cite this

An improved distance measure between the expression profiles linking co-expression and co-regulation in mouse. / Kim, Ryung S.; Ji, Hongkai; Wong, Wing H.

In: BMC Bioinformatics, Vol. 7, 44, 26.01.2006.

Research output: Contribution to journalArticle

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