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Automated Reconstruction of Neuronal Morphology Based on Local Geometrical and Global Structural Models

Overview of attention for article published in Neuroinformatics, May 2011
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Mentioned by

patent
2 patents

Citations

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107 Dimensions

Readers on

mendeley
112 Mendeley
Title
Automated Reconstruction of Neuronal Morphology Based on Local Geometrical and Global Structural Models
Published in
Neuroinformatics, May 2011
DOI 10.1007/s12021-011-9120-3
Pubmed ID
Authors

Ting Zhao, Jun Xie, Fernando Amat, Nathan Clack, Parvez Ahammad, Hanchuan Peng, Fuhui Long, Eugene Myers

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 3 3%
Italy 1 <1%
Australia 1 <1%
Switzerland 1 <1%
Unknown 106 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 35%
Researcher 17 15%
Student > Master 17 15%
Professor 7 6%
Professor > Associate Professor 6 5%
Other 15 13%
Unknown 11 10%
Readers by discipline Count As %
Computer Science 31 28%
Agricultural and Biological Sciences 20 18%
Neuroscience 18 16%
Engineering 17 15%
Physics and Astronomy 5 4%
Other 6 5%
Unknown 15 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 13 September 2023.
All research outputs
#7,551,483
of 23,036,991 outputs
Outputs from Neuroinformatics
#146
of 407 outputs
Outputs of similar age
#40,861
of 110,995 outputs
Outputs of similar age from Neuroinformatics
#1
of 4 outputs
Altmetric has tracked 23,036,991 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 407 research outputs from this source. They receive a mean Attention Score of 4.5. This one has gotten more attention than average, scoring higher than 53% of its peers.
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 110,995 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them