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Saturday, March 6, 2010,
LSE Room 104, Arizona State University Registration fees: $50 students, $75 postdocs, $100 faculty Register here. |
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| Tutorial slides or information: NEURON Slides PSICS Slides NeuronVisio slides Whole Brain Catalog Information |
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Tutorial Schedule: 8:15 Registration Open 8:30 Whole Brain Catalog, Stephen Larson, University of California San Diego 8:50 NeuroTools & Sumatra, Andrew Davison, Centre National de la Recherche Scientifique 9:10 NeuronVisio, Michele Mattioni, European Bioinformatics Institute, UK 9:30 neuroConstruct & NeuroML, Padraig Gleeson, University College London 9:50 Coffee and Continental Breakfast 10:15-11:15 Parallel Sessions
11:30-12:30 Parallel Sessions
Whole Brain Catalog, http://wholebraincatalog.org Make new connections with the Whole Brain Catalog, an open source, downloadable, multiscale, virtual catalog of the mouse brain and its cellular constituents. NeuroTools, http://neuralensemble.org/trac/NeuroTools/ NeuroTools is a collection of tools to support all tasks associated with a neural simulation project, which are not handled by the simulation engine. It provides modules to facilitate simulation setup, parameterization, data management, analysis and visualization. NeuronVisio, http://mattions.github.com/neuronvisio/ NeuronVisio provides a graphical user interface for the NEURON simulation environment that allows for 3-D visualization of the model, the creation of vectors to record any of the variables, Pylab integration to plot directly simulation results, and the exploration of any variable using a color coded scale. neuroConstruct, http://neuroconstruct.org neuroConstruct provides support for developing neuronal network models in 3-D, generating simulation scripts for use in existing simulator environments such as NEURON, GENESIS, MOOSE, PyNN, and PSICS, and automatically generates code to record simulation results for visualization in neuroConstruct. NeuroML, http://neuroml.org NeuroML is a collaborative effort to create a description language for complex models of neurons and neuronal networks. The goals of NeuroML are to facilitate the exchange of complex neural models, allow for greater transparency and accessibility of models, enhance interoperability between simulators and other tools, and support the development of new software and databases. NEURON, http://www.neuron.yale.edu/neuron NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. PyNN, http://neuralensemble.org/trac/PyNN PyNN is a Python-based, simulator independent language for building neuronal network models. In other words, you can write the code for a model once, using the PyNN API and the Python programming language, and then run it without modification on any simulator that PyNN supports (currently NEURON, NEST, PCSIM and Brian). SBML, http://sbml.org The Systems Biology Markup Language (SBML) is a computer-readable format for representing models of biological processes that is applicable to simulations of metabolism, cell signaling, biochemical reactions, gene regulatory networks, and many other topics. PSICS, http://www.psics.org PSICS models the behavior of neurons taking account of the stochastic nature of ion channel gating and the detailed positions of the channels themselves. PSICS is intended to be complementary to existing tools. With its focus on kinetic scheme channel models, stochastic behavior, and detailed geometry, it lives in the space between stochastic diffusion models of small sections of neurons (MCell, STEPS) and deterministic whole cell models (Neuron, Genesis).
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