ReviewNeuroinformatics2007
Interoperability of neuroscience modeling software: current status and future directions.
Review in Neuroinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed.
- Article
- Article
- A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience.Neuroinformatics · 2022Article
- Neuron-Glia Interactions and Brain Circuits.Advances in experimental medicine and biology · 2022Article
- Geppetto: a reusable modular open platform for exploring neuroscience data and models.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018Article
- Computational Models for Calcium-Mediated Astrocyte Functions.Frontiers in computational neuroscience · 2018Review
- Reproducibility and Comparability of Computational Models for Astrocyte Calcium Excitability.Frontiers in neuroinformatics · 2017Article
- Reproducibility in Computational Neuroscience Models and Simulations.IEEE transactions on bio-medical engineering · 2016Article
- libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.Frontiers in neuroinformatics · 2014Article
- Current practice in software development for computational neuroscience and how to improve it.PLoS computational biology · 2014Article
- Reaction-diffusion in the NEURON simulator.Frontiers in neuroinformatics · 2013Article
- Virk: an active learning-based system for bootstrapping knowledge base development in the neurosciences.Frontiers in neuroinformatics · 2013Article
- The connection-set algebra--a novel formalism for the representation of connectivity structure in neuronal network models.Neuroinformatics · 2012Article
- The layer-oriented approach to declarative languages for biological modeling.PLoS computational biology · 2012Article
- A federated design for a neurobiological simulation engine: the CBI federated software architecture.PloS one · 2012Article
- Modeling signal transduction leading to synaptic plasticity: evaluation and comparison of five models.EURASIP journal on bioinformatics & systems biology · 2011Article
- The role of type 4 phosphodiesterases in generating microdomains of cAMP: large scale stochastic simulations.PloS one · 2010Article
- NeuroML: a language for describing data driven models of neurons and networks with a high degree of biological detail.PLoS computational biology · 2010Article
- Run-time interoperability between neuronal network simulators based on the MUSIC framework.Neuroinformatics · 2010Article
- Visualizing neuronal network connectivity with connectivity pattern tables.Frontiers in neuroinformatics · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Neuroscience increasingly uses computational models to assist in the exploration and interpretation of complex phenomena. As a result, considerable effort is invested in the development of software tools and technologies for numerical simulations and for the creation and publication of models. The diversity of related tools leads to the duplication of effort and hinders model reuse. Development practices and technologies that support interoperability between software systems therefore play an important role in making the modeling process more efficient and in ensuring that published models can be reliably and easily reused. Various forms of interoperability are possible including the development of portable model description standards, the adoption of common simulation languages or the use of standardized middleware. Each of these approaches finds applications within the broad range of current modeling activity. However more effort is required in many areas to enable new scientific questions to be addressed. Here we present the conclusions of the "Neuro-IT Interoperability of Simulators" workshop, held at the 11th computational neuroscience meeting in Edinburgh ( July 19-20 2006; http://www.cnsorg.org ). We assess the current state of interoperability of neural simulation software and explore the future directions that will enable the field to advance.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.