matlab and simbiology toolbox 2015 Search Results


simbiology toolbox  (MathWorks Inc)
97
MathWorks Inc simbiology toolbox
One compartment simulations in <t>SimBiology</t> demonstrates robustness to parameter changes. (A) The dynamical changes in the active PKC concentration during the course of simulation performed in NeuroRD (here the averaged values in spine and dendrite shown) and SimBiology show good agreement. (B) The area under the curve (AUC) for molecule activations are estimated for TBS and 20 Hz, and then the ratios of molecule activation for TBS relative to 20Hz are calculated. These ratios are quite similar for NeuroRD and SimBiology simulations. (C, D): Principal sensitive parameters affecting the signature molecules for 20Hz (C) and TBS (D). Y-axis represents the fractional response change for the indicated molecules due to each respective parameter. The following parameter naming convention is used for the x-axis: Kcat_S1xS2 is catalytic rate of the enzyme S1 on substrate S2; kf_S1xS2 is association rate constant (kf) between two molecules S1 and S2; kb_S1xS2 is dissociation rate constant (kb) between two molecules S1 and S2.
Simbiology Toolbox, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 97/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/matlab+and+simbiology+toolbox+2015/pmc06165719-137-11-14?v=MathWorks+Inc
Average 97 stars, based on 1 article reviews
simbiology toolbox - by Bioz Stars, 2026-07
97/100 stars
  Buy from Supplier

Image Search Results


One compartment simulations in SimBiology demonstrates robustness to parameter changes. (A) The dynamical changes in the active PKC concentration during the course of simulation performed in NeuroRD (here the averaged values in spine and dendrite shown) and SimBiology show good agreement. (B) The area under the curve (AUC) for molecule activations are estimated for TBS and 20 Hz, and then the ratios of molecule activation for TBS relative to 20Hz are calculated. These ratios are quite similar for NeuroRD and SimBiology simulations. (C, D): Principal sensitive parameters affecting the signature molecules for 20Hz (C) and TBS (D). Y-axis represents the fractional response change for the indicated molecules due to each respective parameter. The following parameter naming convention is used for the x-axis: Kcat_S1xS2 is catalytic rate of the enzyme S1 on substrate S2; kf_S1xS2 is association rate constant (kf) between two molecules S1 and S2; kb_S1xS2 is dissociation rate constant (kb) between two molecules S1 and S2.

Journal: The European journal of neuroscience

Article Title: Molecular Mechanisms Underlying Striatal Synaptic Plasticity: Relevance to Chronic Alcohol Consumption and Seeking

doi: 10.1111/ejn.13919

Figure Lengend Snippet: One compartment simulations in SimBiology demonstrates robustness to parameter changes. (A) The dynamical changes in the active PKC concentration during the course of simulation performed in NeuroRD (here the averaged values in spine and dendrite shown) and SimBiology show good agreement. (B) The area under the curve (AUC) for molecule activations are estimated for TBS and 20 Hz, and then the ratios of molecule activation for TBS relative to 20Hz are calculated. These ratios are quite similar for NeuroRD and SimBiology simulations. (C, D): Principal sensitive parameters affecting the signature molecules for 20Hz (C) and TBS (D). Y-axis represents the fractional response change for the indicated molecules due to each respective parameter. The following parameter naming convention is used for the x-axis: Kcat_S1xS2 is catalytic rate of the enzyme S1 on substrate S2; kf_S1xS2 is association rate constant (kf) between two molecules S1 and S2; kb_S1xS2 is dissociation rate constant (kb) between two molecules S1 and S2.

Article Snippet: To screen for sensitive model parameters, the model was implemented in SimBiology toolbox of MATLAB (MathsWork) and solved with ode15s solver with a maximum time step of 0.01s in a one compartment morphology using a deterministic approach as in previous work ( Gutierrez-Arenas et al 2014 ; Nair et al 2016 ; Nair et al 2015 ).

Techniques: Concentration Assay, Activation Assay