Title: Modelling and analysis of gene regulatory networks based on the G-network
Authors: Haseong Kim
Addresses: Biochemicals and Synthetic Biology Center, Korea Research Institute of Bioscience and Biotechnology, 125 Gwahak-ro, Yuseong-gu, Daejeon, South Korea
Abstract: G-networks are a class of stochastic models that have had a broad range of applications ranging from the performance analysis of computer systems and networks to the modelling of gene regulatory networks. Gene regulatory networks consist of thousands of genes and proteins which are dynamically interacting with each other. Once these regulatory structures are revealed, it is necessary to understand their dynamical behaviours since pathway activities could be changed by their given conditions. This review mainly focuses on a stochastic GRN modelling techniques based on G-networks which provide the analytical steady-state solution of a system for efficient GRN dynamics modelling. Three applications of the G-network model to GRNs show that this novel approach can serve to detect abnormalities from protein expression data, and that they can help to explicit the behaviour of complicated GRN models by dividing the gene regulatory processes into DNA and protein layers.
Keywords: G-networks; gene regulatory networks; GRNs; stochastic modelling; abnormity detection; protein expression data; DNA layers; protein layers.
International Journal of Advanced Intelligence Paradigms, 2014 Vol.6 No.1, pp.28 - 51
Received: 23 Jan 2013
Accepted: 11 Jul 2013
Published online: 28 Jun 2014 *