Quantitative inference of dynamic regulatory pathways via microarray data

Background: The cellular signaling pathway (network) is one of the main topics of organismic investigations. The intracellular interactions between genes in a signaling pathway are considered as the foundation of functional genomics. Thus, what genes and how much they influence each other through transcriptional binding or physical interactions are essential problems. Under the synchronous measures of gene expression via a microarray chip, an amount of dynamic information is embedded and remains to be discovered. Using a systematically dynamic modeling approach, we explore the causal relationship among genes in cellular signaling pathways from the system biology approach. Results: In this study, a second-order dynamic model is developed to describe the regulatory mechanism of a target gene from the upstream causality point of view. From the expression profile and dynamic model of a target gene, we can estimate its upstream regulatory function. According to this upstream regulatory fun...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Wen-Chieh Chang, Chang-Wei Li, Bor-Sen Chen
• Keywords: BMCBI 2005, Regulatory, Regulatory Pathway, Signaling Pathways