Standard Formats
Displaying: 3 Found: 18 Total: 18
FieldML v0.5
FieldML Version 0.5
Synopsis
Description
The FieldML project has made significant progress towards the goal of addressing the need to have open standards and open source software for representing finite element method (FEM) models and, more generally, multivariate field models, such as many of the models that are core to the euHeart project and the Physiome project. FieldML version 0.5 is the most recently released format from the FieldML project. It is an XML format that already has sufficient capability to represent the majority of euHeart's explicit models such as the anatomical FEM models and simulation solution fields. The details of FieldML version 0.5 are presented, as well as its limitations and some discussion of the progress being made to address these limitations.*
*(Britten RD et al. Medical & Biological Engineering & Computing. 2013;51(11):1191-1207. )
Publication Date
Authors
Organizations
Biological Scales
Scale | molecular | cellular | tissue | organ | organism | ecosystem |
---|---|---|---|---|---|---|
Support | potential | intrinsic | intrinsic | intrinsic | potential | unknown |
Spatial Representation
Spatial Representation Level | Compartment | Dimensions | Gradients | Spatial Structures |
---|---|---|---|---|
Support | intrinsic | intrinsic | intrinsic | intrinsic |
Advantage
- Model components reusability
Modularity: yes
Components Relation
Flat Network:
no
Supported Math
MathML Support: no
Full MathML Support: no
Description
Expressions for higher level mathematical concepts including differential and integrational calculus.
Unit Support
Unit Required: no
Support: no support
Description
Annotation Support
Biological
Application
Format
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FieldML v0.5 |
FieldML
Description
Publication date
Organizations
Links
Webpage
All formats for this class
no license information
MorphML v1.8.1
NeuroML Version 1.8.1 Level 1 MorphML
Synopsis
Description
Biologically detailed single neuron and network models are important for understanding how ion channels, synapses and anatomical connectivity underlie the complex electrical behavior of the brain. [...] We have used an Open Source software approach to develop NeuroML, a neuronal model description language based on XML (Extensible Markup Language). This enables these detailed models and their components to be defined in a standalone form, allowing them to be used across multiple simulators and archived in a standardized format. Here we describe the structure of NeuroML and demonstrate its scope by converting into NeuroML models of a number of different voltage- and ligand-gated conductances, models of electrical coupling, synaptic transmission and short-term plasticity, together with morphologically detailed models of individual neurons. We have also used these NeuroML-based components to develop an highly detailed cortical network model. NeuroML-based model descriptions were validated by demonstrating similar model behavior across five independently developed simulators. Although our results confirm that simulations run on different simulators converge, they reveal limits to model interoperability, by showing that for some models convergence only occurs at high levels of spatial and temporal discretisation, when the computational overhead is high. Our development of NeuroML as a common description language for biophysically detailed neuronal and network models enables interoperability across multiple simulation environments, thereby improving model transparency, accessibility and reuse in computational neuroscience.*
*(Gleeson P et al. PLoS Computational Biology. 2010;6(6))
Publication Date
Authors
Organizations
Biological Scales
Scale | molecular | cellular | tissue | organ | organism | ecosystem |
---|---|---|---|---|---|---|
Support | unknown | intrinsic | unknown | unknown | unknown | unknown |
Spatial Representation
Spatial Representation Level | Compartment | Dimensions | Gradients | Spatial Structures |
---|---|---|---|---|
Support | intrinsic | intrinsic | potential | intrinsic |
Advantage
- Multiscale Models
Modularity: yes
Components Relation
Flat Network:
no
Supported Math
Unit Support
Unit Required: yes
Support: intrinsic
Description
Annotation Support
Miriram Support: no
identifiers.org Support: no
Description
Any kind of XML elements can be used inside the annotation element. Metadata has its own specification.
Links
Specification
Biological
Application
Format
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MorphML v1.8.1 |
Webpage
Model repository
Software Repository
Specification
NeuroML
Description
Model Description Language for Computational Neuroscience
Derived from
Publication date
Organizations
Links
Webpage
All formats for this class
GNU General Public License, version 2
Description
Free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation.
For detailed information see webpage.
Links
NetworkML v1.8.1
NeuroML Version 1.8.1 Level 3 NetworkML
Synopsis
Description
Biologically detailed single neuron and network models are important for understanding how ion channels, synapses and anatomical connectivity underlie the complex electrical behavior of the brain. [...] We have used an Open Source software approach to develop NeuroML, a neuronal model description language based on XML (Extensible Markup Language). This enables these detailed models and their components to be defined in a standalone form, allowing them to be used across multiple simulators and archived in a standardized format. Here we describe the structure of NeuroML and demonstrate its scope by converting into NeuroML models of a number of different voltage- and ligand-gated conductances, models of electrical coupling, synaptic transmission and short-term plasticity, together with morphologically detailed models of individual neurons. We have also used these NeuroML-based components to develop an highly detailed cortical network model. NeuroML-based model descriptions were validated by demonstrating similar model behavior across five independently developed simulators. Although our results confirm that simulations run on different simulators converge, they reveal limits to model interoperability, by showing that for some models convergence only occurs at high levels of spatial and temporal discretisation, when the computational overhead is high. Our development of NeuroML as a common description language for biophysically detailed neuronal and network models enables interoperability across multiple simulation environments, thereby improving model transparency, accessibility and reuse in computational neuroscience.*
*(Gleeson P et al. PLoS Computational Biology. 2010;6(6))
Publication Date
Authors
Organizations
Biological Scales
Scale | molecular | cellular | tissue | organ | organism | ecosystem |
---|---|---|---|---|---|---|
Support | unknown | unknown | intrinsic | intrinsic | unknown | unknown |
Spatial Representation
Spatial Representation Level | Compartment | Dimensions | Gradients | Spatial Structures |
---|---|---|---|---|
Support | intrinsic | intrinsic | unknown | intrinsic |
Advantage
- Multiscale Models
Modularity: yes
Components Relation
Flat Network:
no
Supported Math
Unit Support
Unit Required: yes
Support: intrinsic
Description
Annotation Support
Miriram Support: no
identifiers.org Support: no
Description
Links
Specification
Biological
Application
Format
|
|||||
---|---|---|---|---|---|
NetworkML v1.8.1 |
Webpage
Model repository
Software Repository
Specification
NeuroML
Description
Model Description Language for Computational Neuroscience
Derived from
Publication date
Organizations
Links
Webpage
All formats for this class
GNU General Public License, version 2
Description
Free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation.
For detailed information see webpage.