Report
Integration of rule-based models and compartmental models of neurons
| العنوان: | Integration of rule-based models and compartmental models of neurons |
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| المؤلفون: | Sterratt, David C., Sorokina, Oksana, Armstrong, J. Douglas |
| سنة النشر: | 2014 |
| المجموعة: | Quantitative Biology |
| مصطلحات موضوعية: | Quantitative Biology - Neurons and Cognition |
| الوصف: | Synaptic plasticity depends on the interaction between electrical activity in neurons and the synaptic proteome, the collection of over 1000 proteins in the post-synaptic density (PSD) of synapses. To construct models of synaptic plasticity with realistic numbers of proteins, we aim to combine rule-based models of molecular interactions in the synaptic proteome with compartmental models of the electrical activity of neurons. Rule-based models allow interactions between the combinatorially large number of protein complexes in the postsynaptic proteome to be expressed straightforwardly. Simulations of rule-based models are stochastic and thus can deal with the small copy numbers of proteins and complexes in the PSD. Compartmental models of neurons are expressed as systems of coupled ordinary differential equations and solved deterministically. We present an algorithm which incorporates stochastic rule-based models into deterministic compartmental models and demonstrate an implementation ("KappaNEURON") of this hybrid system using the SpatialKappa and NEURON simulators. Comment: Presented to the Third International Workshop on Hybrid Systems Biology Vienna, Austria, July 23-24, 2014 at the International Conference on Computer-Aided Verification 2014 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1411.4980 |
| رقم الانضمام: | edsarx.1411.4980 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |