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dc.contributor.authorWannige, Champi
dc.contributor.authorKulasiri, Gamalathge D.
dc.contributor.authorSamarasinghe, Sandhya
dc.contributor.editorZhang, W.en
dc.date.accessioned2018-06-18T04:35:45Z
dc.date.issued2013
dc.identifier.citationWannige, T., Kulasiri, D., & Samarasinghe, S. (2013). Modelling stochasticity in multi-stable and oscillatory biological networks far from equilibrium. In W. Zhang (Ed.), Network biology: theories, methods and applications (pp. 163-192). New York: Nova Science Publishers.
dc.identifier.isbn9781626189423en
dc.identifier.urihttps://hdl.handle.net/10182/9665
dc.description.abstractRandom nature of chemical reactions and low copy numbers of participating chemical species originate fluctuations in naturally open biological systems. These inevitable fluctuations drive these open biological systems even in the presence of perturbations to self-organised, dissipative structures far from thermodynamic equilibrium in the presence of inward and outward flows of material, energy and information. Far from equilibrium, biological systems exhibit much complex dynamical behaviour such as multi-stability, oscillations, chaos and fractals and this review focus on the important stochastic modelling issues and approaches relevant to modelling these complex systems with examples. For example, 2MA method provides a robust way to look at the evolution of first two moments and Keizer’s theory provides a mechanistic, statistical framework for modelling fluctuations for large volume systems. Always analytical methods like Chemical Master Equation, Chemical Langevin Equation, Fokker-Plank equation provide more insights into system behaviour as they consider the effect of randomness and the real particle behaviour. Nevertheless, these modelling methods or experimental methods are not yet developed enough to see a meososcopic system’s dynamic behaviour in all parameter ranges in one picture. More efficient, and accurate, modelling and simulation methods which consider the real thermodynamic and mechanistic behaviour of systems are necessarily needed for better understanding of dynamics in meososcopic complex biosystems.en
dc.format.extentpp. 163-192, chapter VII of VIIen
dc.language.isoen
dc.publisherNova Science Publishers
dc.relationThe original publication is available from - Nova Science Publishersen
dc.relation.ispartofseriesSystems biology- Theory, techniques, and applicationsen
dc.rightsCopyright © 2013 by Nova Science Publishers, Inc.
dc.subjectmolecular fluctuationsen
dc.subjectbiological noiseen
dc.subjectstochastic modellingen
dc.subjectthermodynamic modelingen
dc.titleModelling stochasticity in multi-stable and oscillatory biological networks far from equilibriumen
dc.typeBook Chapter
lu.contributor.unitLincoln University
lu.contributor.unitFaculty of Agriculture and Life Sciences
lu.contributor.unitDepartment of Wine, Food and Molecular Biosciences
lu.contributor.unitFaculty of Environment, Society and Design
lu.contributor.unitDepartment of Environmental Management
dc.subject.anzsrc010406 Stochastic Analysis and Modellingen
dc.subject.anzsrc080110 Simulation and Modellingen
dc.relation.isPartOfNetwork biology: Theories, methods and applicationsen
pubs.organisational-group/LU
pubs.organisational-group/LU/Agriculture and Life Sciences
pubs.organisational-group/LU/Agriculture and Life Sciences/WFMB
pubs.organisational-group/LU/Faculty of Environment, Society and Design
pubs.organisational-group/LU/Faculty of Environment, Society and Design/DEM
pubs.organisational-group/LU/Research Management Office
pubs.organisational-group/LU/Research Management Office/QE18
pubs.publication-statusPublisheden
dc.publisher.placeNew Yorken
lu.identifier.orcid0000-0001-8744-1578
lu.identifier.orcid0000-0003-2943-4331
dc.identifier.eisbn9781626189560en


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