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DeepBouton: Automated Identification of Single-Neuron Axonal Boutons at the Brain-Wide Scale

Overview of attention for article published in Frontiers in Neuroinformatics, April 2019
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Mentioned by

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1 Facebook page

Citations

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12 Dimensions

Readers on

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22 Mendeley
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Title
DeepBouton: Automated Identification of Single-Neuron Axonal Boutons at the Brain-Wide Scale
Published in
Frontiers in Neuroinformatics, April 2019
DOI 10.3389/fninf.2019.00025
Pubmed ID
Authors

Shenghua Cheng, Xiaojun Wang, Yurong Liu, Lei Su, Tingwei Quan, Ning Li, Fangfang Yin, Feng Xiong, Xiaomao Liu, Qingming Luo, Hui Gong, Shaoqun Zeng

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 18%
Researcher 4 18%
Student > Ph. D. Student 3 14%
Student > Doctoral Student 2 9%
Unspecified 1 5%
Other 3 14%
Unknown 5 23%
Readers by discipline Count As %
Neuroscience 5 23%
Biochemistry, Genetics and Molecular Biology 2 9%
Computer Science 2 9%
Medicine and Dentistry 2 9%
Unspecified 1 5%
Other 4 18%
Unknown 6 27%
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 03 May 2019.
All research outputs
#20,568,245
of 23,144,579 outputs
Outputs from Frontiers in Neuroinformatics
#688
of 759 outputs
Outputs of similar age
#299,961
of 350,170 outputs
Outputs of similar age from Frontiers in Neuroinformatics
#22
of 27 outputs
Altmetric has tracked 23,144,579 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 759 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 350,170 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.