ArticleBMC systems biology2010
Stochastic and deterministic multiscale models for systems biology: an auxin-transport case study.
Article in BMC systems biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Article
- Fluctuations in auxin levels depend upon synchronicity of cell divisions in a one-dimensional model of auxin transport.PLoS computational biology · 2023Article
- A Holistic Approach from Systems Biology Reveals the Direct Influence of the Quorum-Sensing Phenomenon onMetabolites · 2023Article
- Regenerative medicine meets mathematical modelling: developing symbiotic relationships.NPJ Regenerative medicine · 2021Review
- Spatial Stochastic Intracellular Kinetics: A Review of Modelling Approaches.Bulletin of mathematical biology · 2019Review
- Systems biology: perspectives on multiscale modeling in research on endocrine-related cancers.Endocrine-related cancer · 2019Review
- Single-cell variability in multicellular organisms.Nature communications · 2018Article
- A computational pipeline for identifying kinetic motifs to aid in the design and improvement of synthetic gene circuits.BMC bioinformatics · 2013Article
- Multiscale systems analysis of root growth and development: modeling beyond the network and cellular scales.The Plant cell · 2012Review
- Multiscale modelling of auxin transport in the plant-root elongation zone.Journal of mathematical biology · 2012Article
- Exploring behaviors of stochastic differential equation models of biological systems using change of measures.BMC bioinformatics · 2012Article
- The Infobiotics Workbench: an integrated in silico modelling platform for Systems and Synthetic Biology.Bioinformatics (Oxford, England) · 2011Article
- A thermodynamic switch modulates abscisic acid receptor sensitivity.The EMBO journal · 2011Article
- The ten grand challenges of synthetic life.Systems and synthetic biology · 2011Article
- Evolving cell models for systems and synthetic biology.Systems and synthetic biology · 2010Article
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Authors and funding
5 authors.
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Abstract
backgroundStochastic and asymptotic methods are powerful tools in developing multiscale systems biology models; however, little has been done in this context to compare the efficacy of these methods. The majority of current systems biology modelling research, including that of auxin transport, uses numerical simulations to study the behaviour of large systems of deterministic ordinary differential equations, with little consideration of alternative modelling frameworks.
resultsIn this case study, we solve an auxin-transport model using analytical methods, deterministic numerical simulations and stochastic numerical simulations. Although the three approaches in general predict the same behaviour, the approaches provide different information that we use to gain distinct insights into the modelled biological system. We show in particular that the analytical approach readily provides straightforward mathematical expressions for the concentrations and transport speeds, while the stochastic simulations naturally provide information on the variability of the system.
conclusionsOur study provides a constructive comparison which highlights the advantages and disadvantages of each of the considered modelling approaches. This will prove helpful to researchers when weighing up which modelling approach to select. In addition, the paper goes some way to bridging the gap between these approaches, which in the future we hope will lead to integrative hybrid models.
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