ArticleFrontiers in neuroinformatics2014
Python-based geometry preparation and simulation visualization toolkits for STEPS.
Article in Frontiers in neuroinformatics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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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.
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Who cites it
2 citing papers in PubMed.
- Influence of T-Bar on Calcium Concentration Impacting Release Probability.Frontiers in computational neuroscience · 2022Article
- Spines slow down dendritic chloride diffusion and affect short-term ionic plasticity of GABAergic inhibition.Scientific reports · 2016Article
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Authors and funding
2 authors.
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Abstract
STEPS is a stochastic reaction-diffusion simulation engine that implements a spatial extension of Gillespie's Stochastic Simulation Algorithm (SSA) in complex tetrahedral geometries. An extensive Python-based interface is provided to STEPS so that it can interact with the large number of scientific packages in Python. However, a gap existed between the interfaces of these packages and the STEPS user interface, where supporting toolkits could reduce the amount of scripting required for research projects. This paper introduces two new supporting toolkits that support geometry preparation and visualization for STEPS simulations.
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Registered trials
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