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Title 

Modelling and analysis of gene regulatory networks based on the G-network

Authors 

Haseong Kim

Publisher 

Inderscience

Issue Date 

2014

Citation 

International Journal of Advanced Intelligence Paradigms, vol. 6, no. 1, pp. 28-51

Keywords 

Abnormity detectionG-networksGene regulatory networksGRNsStochastic modelling

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.

ISSN 

1755-0386

Link 

http://dx.doi.org/10.1504/IJAIP.2014.059585

Appears in Collections

1. Journal Articles > Journal Articles

Registered Date

2019-05-02


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