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density functional theory calculations  (MathWorks Inc)


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    MathWorks Inc density functional theory calculations
    Density Functional Theory Calculations, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 97/100, based on 559 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/density functional theory calculations/product/MathWorks Inc
    Average 97 stars, based on 559 article reviews
    density functional theory calculations - by Bioz Stars, 2026-04
    97/100 stars

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    An overview of available software packages and tools used by the Subcellular Workflow. Sometimes, manual intervention is needed in between workflow modules. This is especially true when an input format does not have a feature that an output format has. Additionally, some software packages have so many functions that it could be easier to use them interactively (in these cases we also added a yes in the manual intervention column)

    Journal: Neuroinformatics

    Article Title: A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

    doi: 10.1007/s12021-021-09546-3

    Figure Lengend Snippet: An overview of available software packages and tools used by the Subcellular Workflow. Sometimes, manual intervention is needed in between workflow modules. This is especially true when an input format does not have a feature that an output format has. Additionally, some software packages have so many functions that it could be easier to use them interactively (in these cases we also added a yes in the manual intervention column)

    Article Snippet: Another way to convert the model into SBML is through a single MATLAB® SimBiology® function.

    Techniques: Software, Plasmid Preparation, Functional Assay

    Simulations in identical conditions in both MATLAB® SimBiology® and COPASI yielded almost identical results. A Inputs used in both simulators. The calcium input is kept constant at 4 s for all simulations and dopamine input time is varied from time 0 to 8 s at every one second. The difference from the previous simulations is in the calcium input which, for the sake of simplicity, is represented by a double exponential spike. B and C show substrate phosphorylation curves analogous to Fig. , the red line represents results obtained in MATLAB® and blue line results from simulations in COPASI. A single 30 s simulation took around 10 s of compute time within a 1 fl spine volume (Intel® Core™ i7-8750H)

    Journal: Neuroinformatics

    Article Title: A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

    doi: 10.1007/s12021-021-09546-3

    Figure Lengend Snippet: Simulations in identical conditions in both MATLAB® SimBiology® and COPASI yielded almost identical results. A Inputs used in both simulators. The calcium input is kept constant at 4 s for all simulations and dopamine input time is varied from time 0 to 8 s at every one second. The difference from the previous simulations is in the calcium input which, for the sake of simplicity, is represented by a double exponential spike. B and C show substrate phosphorylation curves analogous to Fig. , the red line represents results obtained in MATLAB® and blue line results from simulations in COPASI. A single 30 s simulation took around 10 s of compute time within a 1 fl spine volume (Intel® Core™ i7-8750H)

    Article Snippet: Another way to convert the model into SBML is through a single MATLAB® SimBiology® function.

    Techniques: