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      SimTracker tool and code template to design, manage and analyze neural network model simulations in parallel NEURON

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      bioRxiv

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          Abstract

          Advances in technical computing enable larger and more detailed neural models that can incorporate ever more of the rapidly expanding body of quantitative neuroscience data. In principle, such complex network models that are strongly constrained by experimental data could direct experimental research and provide novel insights into experimental observations. However, as network models grow in complexity and scale, the necessary tasks of development and organization become unwieldy. Further, the models risk becoming inaccessible to experimentalists and other modelers, and their results may then be seen as less relevant to experimental work. To address these obstacles, we developed a tool for managing simulations called SimTracker. It supports users at each step of the modeling process, including execution of large scale parallel models on supercomputers. SimTracker is suitable for users with a range of modeling experience. SimTracker can be a valuable modeling resource that promotes iterative progress between experiment and model.

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          Author and article information

          Journal
          bioRxiv
          October 19 2016
          Article
          10.1101/081927
          8c46c95c-7071-4719-b261-cddfa655a8ed
          © 2016
          History

          Molecular medicine,Neurosciences
          Molecular medicine, Neurosciences

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