Welcome to the German Neuroinformatics Node

The global scale of neuroinformatics offers unprecedented opportunities for scientific collaborations between and among experimental and theoretical neuroscientists. To fully harvest these possibilities, coordinated activities are required to improve key ingredients of neuroscience: data access, data storage, and data analysis, together with supporting activities for teaching and training.

Focusing on the development and free distribution of tools for handling and analyzing neurophysiological data, G-Node aims at addressing these aspects as part of the International Neuroinformatics Coordinating Facility (INCF) and the German Bernstein Network for Computational Neuroscience (NNCN). G-Node also serves as an international forum for Computational Neuroscientists that are interested in sharing experimental data and tools for data analysis and modeling. G-Node is funded through the German Federal Ministry of Education and Research and hosted by Ludwig-Maximilians-Universität München.

 


News

10ᵗʰ Advanced Scientific Programming in Python

Nikiti, Greece, August 28 - September 2, 2017

Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist.

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G-Node Advanced Neural Data Analysis Course: ANDA 2018

Jülich, March 5 - 22, 2018

Techniques to record neuronal data from populations of neurons are rapidly improving. Simultaneous recordings from hundreds of channels are possible while animals perform complex behavioral tasks. The analysis of such massive and complex data becomes increasingly challenging. This advanced course aims at providing deeper training in state-of-the-art analysis approaches in systems neuroscience.

Application deadline: Oct 15, 2017

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