We conduct the transcription factor (TF) analysis by detecting transcription factor pairs and incorporating binding positions for genes with altered expressions in time-series cDNA microarray data. Prediction of TF pairs that mostly likely contribute to the regulated transcription of differentially expressed genes are done through the computation of their expression coherence (EC). The Expectation Maximization (EM) clustering is performed additionally in order to detect patterns in specific TF binding positions. We evaluate the EC of expression profiles of genes within each cluster to discover binding trends that may play a significant role in regulation of target genes. Our method has successfully identified TF pairs that have a greater potential for regulating their target genes at specified locations rather than at arbitrary locations.
Date:
2007-05
Relation:
Systems Biology and Regulatory Genomics. 2007 May;4023 LNBI:138-149.
