Woken

Woken provides a web service and an API to execute on demand data analytics and machine learning algorithms encapsulated in Docker containers. Algorithms and their runtime are fetched from the Algorithm Repository, a Docker registry containing approved and compatible algorithms and their runtimes. Woken provides the algorithms with data loaded from a database, monitors the execution of the algorithm other one machine of a cluster, then it collects the result formatted as a PFA document and returns a response to the client. Woken tracks provenance information, runs cross-validation of the models produced by the ML algorithms.

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Source Code
Contributors
CG GC AJ MN LC

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siibra-explorer

siibra-explorer is built around an interactive 3D view of the brain displaying a unique selection of detailed templates and parcellation maps for the human, macaque, rat or mouse brain, including BigBrain as a microscopic resolution human brain model at its full resolution of 20 micrometres.

Collaboratory

The EBRAINS Collaboratory offers researchers and developers a secure environment to work with others. You control the level of collaboration by sharing your projects with specific users, teams or all of the Internet. Many researchers are sharing their work already; several services, tools, datasets and other resources are publicly available, and many more are available for registered users.

MeshView

MeshView is a web application for real-time 3D display of surface mesh data representing structural parcellations from volumetric atlases, such as the Waxholm Space Atlas of the Sprague Dawley Rat Brain. MeshView is available as an EBRAINS community app, accessible via a collab (further info: https://wiki.ebrains.eu/bin/view/Collabs/image-registration-and-analysis-demo/) Key features: orbiting view with toggleable opaque/transparent/hidden parcellation meshes rendering user defined cut surface as if meshes were solid objects rendering point-clouds (simple type-in, or loaded from a JSON format) coordinate system is compatible with QuickNII (https://www.nitrc.org/projects/quicknii)

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