Inferring activity changes of transcription factors by binding association with sorted expression profiles

Background: The identification of transcription factors (TFs) associated with a biological process is fundamental to understanding its regulatory mechanisms. From microarray data, however, the activity changes of TFs often cannot be directly observed due to their relatively low expression levels, post-transcriptional modifications, and other complications. Several approaches have been proposed to infer TF activity changes from microarray data. In some models, a linear relationship between gene expression and TF-gene binding strength is assumed. In some other models, the target genes of a TF are first determined by a significance cutoff to binding affinity scores, and then expression differentiation is checked between the target and other genes. Results: We propose a novel method, referred to as BASE (binding association with sorted expression), to infer TF activity changes from microarray expression profiles with the help of binding affinity data. It searches the maximum association b...

• Type: Journal
• Year: 2007
• Where: BMCBI
• Authors: Chao Cheng, Xiting Yan, Fengzhu Sun, Lei M. Li
• Keywords: Affinity Data, BMCBI 2007, Microarray Data, TF Activity