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Multi-labelled proteins recognition for high-throughput microscopy images using deep convolutional neural networks

Overview of attention for article published in BMC Bioinformatics, June 2021
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (55th percentile)

Mentioned by

twitter
6 X users

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
8 Mendeley
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Title
Multi-labelled proteins recognition for high-throughput microscopy images using deep convolutional neural networks
Published in
BMC Bioinformatics, June 2021
DOI 10.1186/s12859-021-04196-3
Pubmed ID
Authors

Enze Zhang, Boheng Zhang, Shaohan Hu, Fa Zhang, Zhiyong Liu, Xiaohua Wan

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Researcher 2 25%
Unspecified 1 13%
Student > Master 1 13%
Unknown 2 25%
Readers by discipline Count As %
Computer Science 2 25%
Biochemistry, Genetics and Molecular Biology 2 25%
Unspecified 1 13%
Unknown 3 38%
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 17 November 2021.
All research outputs
#13,527,742
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#4,095
of 7,388 outputs
Outputs of similar age
#195,462
of 446,623 outputs
Outputs of similar age from BMC Bioinformatics
#110
of 159 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,388 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 42nd percentile – i.e., 42% 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 446,623 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.
We're also able to compare this research output to 159 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.