Trimming of mammalian transcriptional networks using network component analysis

Background: Network Component Analysis (NCA) has been used to deduce the activities of transcription factors (TFs) from gene expression data and the TF-gene binding relationship. However, the TF-gene interaction varies in different environmental conditions and tissues, but such information is rarely available and cannot be predicted simply by motif analysis. Thus, it is beneficial to identify key TF-gene interactions under the experimental condition based on transcriptome data. Such information would be useful in identifying key regulatory pathways and gene markers of TFs in further studies. Results: We developed an algorithm to trim network connectivity such that the important regulatory interactions between the TFs and the genes were retained and the regulatory signals were deduced. Theoretical studies demonstrated that the regulatory signals were accurately reconstructed even in the case where only three independent transcriptome datasets were available. At least 80% of the main ta...

• Type: Journal
• Year: 2010
• Where: BMCBI
• Authors: Linh M. Tran, Daniel R. Hyduke, James C. Liao
• Keywords: BMCBI 2010, Regulatory, Tf-gene Interactions, Transcriptome Data