ArticlePhysical biology2015
Model reduction for stochastic CaMKII reaction kinetics in synapses by graph-constrained correlation dynamics.
Article in Physical biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Interactions between calmodulin and neurogranin govern the dynamics of CaMKII as a leaky integrator.PLoS computational biology · 2020Article
- A multi-state model of the CaMKII dodecamer suggests a role for calmodulin in maintenance of autophosphorylation.PLoS computational biology · 2019Article
- Prospects for Declarative Mathematical Modeling of Complex Biological Systems.Bulletin of mathematical biology · 2019Article
- Learning moment closure in reaction-diffusion systems with spatial dynamic Boltzmann distributions.Physical review. E · 2019Article
- Multi-scale stochastic organization-oriented coarse-graining exemplified on the human mitotic checkpoint.Scientific reports · 2019Article
- Learning dynamic Boltzmann distributions as reduced models of spatial chemical kinetics.The Journal of chemical physics · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
A stochastic reaction network model of Ca(2+) dynamics in synapses (Pepke et al PLoS Comput. Biol. 6 e1000675) is expressed and simulated using rule-based reaction modeling notation in dynamical grammars and in MCell. The model tracks the response of calmodulin and CaMKII to calcium influx in synapses. Data from numerically intensive simulations is used to train a reduced model that, out of sample, correctly predicts the evolution of interaction parameters characterizing the instantaneous probability distribution over molecular states in the much larger fine-scale models. The novel model reduction method, 'graph-constrained correlation dynamics', requires a graph of plausible state variables and interactions as input. It parametrically optimizes a set of constant coefficients appearing in differential equations governing the time-varying interaction parameters that determine all correlations between variables in the reduced model at any time slice.
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Registered trials
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