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.
Advanced Scientific Programming in Python
Split, Croatia, September 8 - 13, 2014; Application deadline May 1, 2014
This course will present a selection of advanced programming techniques with theoretical lectures and practical exercises tailored to the needs of a programming scientist.more
Bernstein Conference 2014 - Call for workshop proposals
Deadline March 1, 2014
The Bernstein Network invites proposals for the Workshops directly preceding the main Bernstein Conference 2014 in Göttingen.more
Training in Neuroinformatics 2015 - Call for Letters of Intent
Deadline March 7, 2014
INCF invites applications to run short courses on any aspects of neuroinformatics at a level suitable for PhD students and beyond.more
6th G-Node Winter Course on Neural Data Analysis
Munich, Feb 24 - 28, 2014
The German Neuroinformatics Node (G-Node) organizes its sixth international training course to promote state-of-the-art methods of neural data analysis among PhD students and postdocs. The course offers hands-on experience with model-driven analysis of data from intra- and extracellular electrophysiology. We encourage applications from students/postdocs with an experimental background that want to widen their repertoire of analysis methods, as well as from students with a theoretical background that have an interest in analyzing physiological data.more