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Philos Trans R Soc Lond B Biol Sci. 2018 Sep 10;373(1758). pii: 20170380. doi: 10.1098/rstb.2017.0380.

Geppetto: a reusable modular open platform for exploring neuroscience data and models.

Author information

1
OpenWorm Foundation, USA matteo@openworm.org.
2
MetaCell Limited, UK.
3
Department of Neuroscience, Physiology and Pharmacology, University College London, UK.
4
Departamento de Física, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Brazil.
5
EyeSeeTea Limited, UK.
6
Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, Edinburgh, UK.
7
Department of Physiology and Pharmacology, SUNY Downstate, Brooklyn, NY, USA.
8
OpenWorm Foundation, USA.

Abstract

Geppetto is an open-source platform that provides generic middleware infrastructure for building both online and desktop tools for visualizing neuroscience models and data and managing simulations. Geppetto underpins a number of neuroscience applications, including Open Source Brain (OSB), Virtual Fly Brain (VFB), NEURON-UI and NetPyNE-UI. OSB is used by researchers to create and visualize computational neuroscience models described in NeuroML and simulate them through the browser. VFB is the reference hub for Drosophila melanogaster neural anatomy and imaging data including neuropil, segmented neurons, microscopy stacks and gene expression pattern data. Geppetto is also being used to build a new user interface for NEURON, a widely used neuronal simulation environment, and for NetPyNE, a Python package for network modelling using NEURON. Geppetto defines domain agnostic abstractions used by all these applications to represent their models and data and offers a set of modules and components to integrate, visualize and control simulations in a highly accessible way. The platform comprises a backend which can connect to external data sources, model repositories and simulators together with a highly customizable frontend.This article is part of a discussion meeting issue 'Connectome to behaviour: modelling C. elegans at cellular resolution'.

KEYWORDS:

computational biology; computational neuroscience; data visualization; modelling and simulation; neuroinformatics; scientific software

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