Neuroinformatics is a research field concerned with the processing and organization of neuroscience data by the application of principles of computer science and state of the art software design methodologies.
Neuroinformatics provides generic and interoperable computational tools, mathematical models, and databases for Neurosciences.
With the diversity of the data generated in neuroscience, going from the genetic and molecular level to cognitive functions and the diversity of acquisition systems, the necessity of developing software tools, standards to describe the data and proper models appears crucial for a better integration of these heterogeneous data for further understanding the brain.
What is INCF?
INCF is an international network of national nodes with neuroinformatics expertise and infrastructure to support collaboration throughout the global brain research community. The mission of INCF is to accelerate advances in understanding and treating the brain through the development of neuroinformatics – applying the best practices of data science to challenges in basic and clinical brain research. The INCF network consists of
Governing Nodes: Australia, Japan, Malaysia, Norway, Sweden
Associated Nodes: Belgium, Czech Republic, Finland, France, Germany, India, Italy, Republic of Korea, Netherlands, Poland, United Kingdom, USA
April 4, 2017
February 28, 2017
February 28, 2017
FENS Jobs Market
- Post-doctoral position in Amsterdam/Netherlands
- Post-doctoral position in TOURS/France
- Post-doctoral position in IRVINE, CALIFORNIA/USA
- Professor in Charlottetown/Canada
- Registration for Neuroinformatics 2017 is now open!
- Abstract submission for Neuroinformatics 2017 is open!
- Videos from Stockholm Brainhack Global 2017
- Canada joins INCF
- Call for seed funding proposals
Recent Neuroinformatics papers
- A Web Resource for Levodopa-Induced Dyskinesia Genetics in Parkinson’s Disease
- Improved Automatic Segmentation of White Matter Hyperintensities in MRI Based on Multilevel Lesion Features
- A Comparison of Accelerated and Non-accelerated MRI Scans for Brain Volume and Boundary Shift Integral Measures of Volume Change: Evidence from the ADNI Dataset
- Multi-View Ensemble Classification of Brain Connectivity Images for Neurodegeneration Type Discrimination
- A Framework for Collaborative Curation of Neuroscientific Literature
- Pypes: Workflows for Processing Multimodal Neuroimaging Data
- The Topographical Mapping in Drosophila Central Complex Network and Its Signal Routing
- Applying an Archetype-Based Approach to Electroencephalography/Event-Related Potential Experiments in the EEGBase Resource