Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data

Background: Integrating data from multiple global assays and curated databases is essential to understand the spatiotemporal interactions within cells. Different experiments measure cellular processes at various widths and depths, while databases contain biological information based on established facts or published data. Integrating these complementary datasets helps infer a mutually consistent transcriptional regulatory network (TRN) with strong similarity to the structure of the underlying genetic regulatory modules. Decomposing the TRN into a small set of recurring regulatory patterns, called network motifs (NM), facilitates the inference. Identifying NMs defined by specific transcription factors (TF) establishes the framework structure of a TRN and allows the inference of TF-target gene relationship. This paper introduces a computational framework for utilizing data from multiple sources to infer TF-target gene relationships on the basis of NMs. The data include time course gene ...

• Type: Journal
• Year: 2008
• Where: BMCBI
• Authors: Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Robert Clarke, Habtom W. Ressom
• Keywords: BMCBI 2008, Gene, Gene Expression, TF-target Gene