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Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit
Linköping University, Department of Physics, Chemistry and Biology. Linköping University, The Institute of Technology.
Linköping University, Department of Physics, Chemistry and Biology. Linköping University, The Institute of Technology.
Stockholm University.
Karolinska University Hospital.
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2009 (English)In: IET SYSTEMS BIOLOGY, ISSN 1751-8849 , Vol. 3, no 2, 113-23 p.Article in journal (Refereed) Published
Abstract [en]

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a tearing-and-zooming approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits.

Place, publisher, year, edition, pages
2009. Vol. 3, no 2, 113-23 p.
National Category
Natural Sciences
URN: urn:nbn:se:liu:diva-17614DOI: 10.1049/iet-syb.2007.0028OAI: diva2:210910
Available from: 2009-04-07 Created: 2009-04-06 Last updated: 2009-04-07

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Eriksson, OliviaBrinne, BjörnTegnér , Jesper
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