BioNetGen 2.2: advances in rule-based modeling

Harris, Leonard A.; Hogg, Justin; Tapia, Jose-Juan; Sekar, John A. P.; Gupta, Sheena; Korsunsky, Ilya; Arora, Arshi; Barua, Dipak; Sheehan, Richard G.; Faeder, James R.

doi:10.1093/bioinformatics/btw469

Cited by 213 publications

(231 citation statements)

References 26 publications

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“…Future work with other substrates is needed to determine whether, and in what context, bivalent reactions can take place with an active PTP domain. Although the strength of our assay is the ability to simultaneously parse multiple parameters, mathematical models based on rule-based frameworks ( 36 , 37 ) are ultimately needed to translate the parameters we obtained into the diverse reactions taking place within cells.…”

Section: Discussionmentioning

confidence: 99%

Biophysical assay for tethered signaling reactions reveals tether-controlled activity for the phosphatase SHP-1

et al. 2017

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Section: Discussionmentioning

confidence: 99%

Biophysical assay for tethered signaling reactions reveals tether-controlled activity for the phosphatase SHP-1

et al. 2017

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“…Moreover, BioNetFit can potentially be used with traditionally formulated models (e.g. ODE models), because BioNetGen has the capability to translate models encoded in the SBML format (Hucka et al, 2003) into BNGL format (Harris et al, 2015). Importantly, BioNetFit is designed to take advantage of distributed computing resources, which can make fitting feasible even when simulation runs are computationally expensive.…”

Section: Discussionmentioning

confidence: 99%

“…Collections of rules form rule-based models, which provide concise representations of biomolecular interaction networks and can be analyzed to obtain insights into how system-level behavior emerges from biomolecular interactions (Chylek et al, 2014a;Stefan et al, 2014). Rule-based models must be analyzed with specialized algorithms and software tools (Chylek et al, 2014a;Stefan et al, 2014), such as BioNetGen (Harris et al, 2015), which interprets models encoded in the BioNetGen language (BNGL) and provides deterministic, stochastic and hybrid forward simulation capabilities (Harris et al, 2015). To date, other critical methods of analysis, such as fitting (parameter estimation), have typically been applied ad hoc (e.g.…”

Section: Introductionmentioning

confidence: 99%

BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

et al. 2015

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Summary: Rule-based models are analyzed with specialized simulators, such as those provided by the BioNetGen and NFsim open-source software packages. Here, we present BioNetFit, a general-purpose fitting tool that is compatible with BioNetGen and NFsim. BioNetFit is designed to take advantage of distributed computing resources. This feature facilitates fitting (i.e. optimization of parameter values for consistency with data) when simulations are computationally expensive. Availability and implementation: BioNetFit can be used on stand-alone Mac, Windows/Cygwin, and Linux platforms and on Linux-based clusters running SLURM, Torque/PBS, or SGE. The BioNetFit source code (Perl) is freely available (http://bionetfit.nau.edu).

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“…Since each CaMKII monomer can bind a calmodulin molecule, which can adopt 9 distinct states (assuming that the 2 Ca 2+ binding sites on each of the lobes are indistinguishable), and be phosphorylated or unphosphorylated, there are more than 18 12 states the dodecameric holoenzyme could adopt. To avoid a combinatorial explosion we built our model in a rule-based modeling language BioNetGen [29], which is briefly describe here.…”

Section: Rule-based Modeling and Bionetgenmentioning

confidence: 99%

Interactions between calmodulin and neurogranin govern the dynamics of CaMKII as a leaky integrator

Ordyan

Bartol

Kennedy

et al. 2019

Preprint

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Calmodulin-dependent kinase II (CaMKII) has long been known to play an important role in learning and memory as well as long term potentiation (LTP). More recently it has been suggested that it might be involved in the time averaging of synaptic signals, which can then lead to the high precision of the information stored at a single synapse. However, the role of the scaffolding molecule, neurogranin (Ng), in governing the dynamics of CaMKII are not yet fully understood. In this work, we adopt a rule-based modeling approach through the Monte Carlo method to study the effect of Ca 2+ signals on the dynamics of CaMKII phosphorylation in the postsynaptic densities (PSD). Calcium surges are observed in the synaptic spines during an EPSP and back-propagating action potential due to the opening of NMDA receptors and voltage dependent calcium channels. We study the differences between the dynamics of phosphorylation of CaMKII monomers and dodecameric holoenzymes. The scaffolding molecule Ng, when present in significant concentration, limits the availability of free calmodulin (CaM), the protein which activates CaMKII in the presence of calcium. We show that it plays an important modulatory role in CaMKII phosphorylation following a surge of high calcium concentration. We find a non-intuitive dependence of this effect on CaM concentration that results from the different affinities of CaM for CaMKII depending on the number of calcium ions bound to the former. It has been shown previously that in the absence 1 2 of phosphatase CaMKII monomers integrate over Ca 2+ signals of certain frequencies through autophosphorylation (Pepke et al, Plos Comp. Bio., 2010). We also study the effect of multiple calcium spikes on CaMKII holoenzyme autophosphorylation, and show that in the presence of phosphatase CaMKII behaves as a leaky integrator of calcium signals, a result that has been recently observed in vivo. Our models predict that the parameters of this leaky integrator are finely tuned through the interactions of Ng, CaM, CaMKII, and PP1. This is a possible mechanism to precisely control the sensitivity of synapses to calcium signals. IntroductionInformation is stored in the brain through synaptic plasticity. It has been reported that synaptic strength is highly correlated with the size of the spine head, and the precision of information stored at a single synapse is much higher than one might have expected, given the stochastic variability of synaptic activation [4,48,44]. Structural changes to the postsynaptic spine that can lead to spine enlargement and thus structural plasticity are triggered by Ca 2+ signaling [30,47].Time averaging of these calcium signals has been suggested as a plausible mechanism for achieving the high precision of information processing observed in spines. Furthermore, phosphorylation of calcium/calmodulin-dependent protein kinase II (CaMKII) has been postulated as the most probable pathway satisfying the long time scales predicted for averaging [4].CaMKII is an autophosphorylating kinase; in postsynapti...

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BioNetGen 2.2: advances in rule-based modeling

Cited by 213 publications

References 26 publications

Biophysical assay for tethered signaling reactions reveals tether-controlled activity for the phosphatase SHP-1

Biophysical assay for tethered signaling reactions reveals tether-controlled activity for the phosphatase SHP-1

BioNetFit: a fitting tool compatible with BioNetGen, NFsim and distributed computing environments

Interactions between calmodulin and neurogranin govern the dynamics of CaMKII as a leaky integrator

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