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3D Brain Atlas Reconstructor Service—Online Repository of Three-Dimensional Models of Brain Structures

Overview of attention for article published in Neuroinformatics, August 2013
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Title
3D Brain Atlas Reconstructor Service—Online Repository of Three-Dimensional Models of Brain Structures
Published in
Neuroinformatics, August 2013
DOI 10.1007/s12021-013-9199-9
Pubmed ID
Authors

Piotr Majka, Jakub M. Kowalski, Natalia Chlodzinska, Daniel K. Wójcik

Abstract

Brain atlases are important tools of neuroscience. Traditionally prepared in paper book format, more and more commonly they take digital form which extends their utility. To simplify work with different atlases, to lay the ground for developing universal tools which could abstract from the origin of the atlas, efforts are being made to provide common interfaces to these atlases. 3D Brain Atlas Reconstructor service (3dBARs) described here is a repository of digital representations of different brain atlases in CAF format which we recently proposed and a repository of 3D models of brain structures. A graphical front-end is provided for creating and viewing the reconstructed models as well as the underlying 2D atlas data. An application programming interface (API) facilitates programmatic access to the service contents from other websites. From a typical user's point of view, 3dBARs offers an accessible way to mine publicly available atlasing data with a convenient browser based interface, without the need to install extra software. For a developer of services related to brain atlases, 3dBARs supplies mechanisms for enhancing functionality of other software. The policy of the service is to accept new datasets as delivered by interested parties and we work with the researchers who obtain original data to make them available to the neuroscience community at large. The functionality offered by the 3dBARs situates it at the core of present and future general atlasing services tying it strongly to the global atlasing neuroinformatics infrastructure.

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Mendeley readers

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The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
France 1 2%
Unknown 45 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 23%
Student > Bachelor 8 17%
Student > Master 7 15%
Student > Ph. D. Student 6 13%
Professor 4 9%
Other 6 13%
Unknown 5 11%
Readers by discipline Count As %
Neuroscience 9 19%
Computer Science 9 19%
Engineering 8 17%
Agricultural and Biological Sciences 6 13%
Medicine and Dentistry 3 6%
Other 6 13%
Unknown 6 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 August 2013.
All research outputs
#18,343,746
of 22,716,996 outputs
Outputs from Neuroinformatics
#319
of 402 outputs
Outputs of similar age
#146,789
of 196,389 outputs
Outputs of similar age from Neuroinformatics
#5
of 6 outputs
Altmetric has tracked 22,716,996 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 402 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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