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2		-== Welcome to the single entry point to user-level documentation for EBRAINS tools and services. Here, you can find a list of EBRAINS offerings, sorted by topic, and their documentation links. ==
	2	+== Findable. Accessible. User-facing. ==
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	5	+=== Welcome to the single entry point to user-level documentation for EBRAINS tools and services. Here, you can find a list of EBRAINS offerings, sorted by topic, and their documentation links. ===
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7	7	=== Collaboratory ===
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9	9	|**[[Collaboratory>>url:https://wiki.ebrains.eu/bin/view/Collabs/the-collaboratory/]]**
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27	27	|**[[siibra-explorer>>url:https://siibra-explorer.readthedocs.io/en/latest/]]**
28	28	siibra-explorer is a browser-based viewer for the visual exploration of the EBRAINS atlases at microscopic detail, as well as the discovery of related multimodal data features. It is tightly integrated with the EBRAINS Knowledge Graph, allowing the seamless querying of semantically and spatially anchored datasets.|**[[QuickNII>>url:https://wiki.ebrains.eu/bin/view/Collabs/quicknii-and-visualign]]**
29	29	QuickNII is a tool for user guided affine registration (anchoring) of 2D experimental image data, typically high resolution microscopic images, to 3D atlas reference space, facilitating data integration through standardized coordinate systems.|**[[VoluBA>>url:https://voluba-user-doc.apps-dev.hbp.eu/]]**
30		-VoluBA (Volumetric Brain Anchoring) is an online service for anchoring of high-resolution volumes of interest from imaging experiments to very large reference volumes.|**[[siibra-python>>url:https://siibra-python.readthedocs.io/en/latest/]]**
	33	+volumetric brain anchoring|**[[siibra-python>>url:https://siibra-python.readthedocs.io/en/latest/]]**
31	31	siibra-python is a comprehensive Python client providing access to EBRAINS atlases and offering an easy and well-structured way to include maps, reference templates, region definitions and linked datasets in reproducible programmatic workflows.
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33	33	=== Data analysis ===
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47	47
48	48	=== Simulation ===
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50		-|[[**Arbor**>>url:https://docs.arbor-sim.org]]
	53	+|**[[Arbor>>url:https://arbor.readthedocs.io/en/v0.5/]]**
51	51	Arbor is a library for implementing performance portable network simulations of multi-compartment neuron models.|**[[BluePyMM>>url:https://bluepymm.readthedocs.io/en/latest/index.html]]**
52	52	Model Management Python Library|**[[BluePyOpt>>url:https://bluepyopt.readthedocs.io/en/latest/]]**
53	53	BluePyOpt is an extensible framework for data-driven model parameter optimisation that wraps and standardizes several existing open-source tools.|