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PIXER: an automated particle-selection method based on segmentation using a deep neural network

Overview of attention for article published in BMC Bioinformatics, January 2019
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

twitter
4 tweeters

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
33 Mendeley
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Title
PIXER: an automated particle-selection method based on segmentation using a deep neural network
Published in
BMC Bioinformatics, January 2019
DOI 10.1186/s12859-019-2614-y
Pubmed ID
Authors

Jingrong Zhang, Zihao Wang, Yu Chen, Renmin Han, Zhiyong Liu, Fei Sun, Fa Zhang

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 24%
Student > Ph. D. Student 8 24%
Other 3 9%
Student > Master 3 9%
Student > Bachelor 2 6%
Other 2 6%
Unknown 7 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 21%
Agricultural and Biological Sciences 7 21%
Computer Science 3 9%
Engineering 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 4 12%
Unknown 9 27%

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 20 January 2019.
All research outputs
#8,875,804
of 14,162,573 outputs
Outputs from BMC Bioinformatics
#3,651
of 5,343 outputs
Outputs of similar age
#185,765
of 319,168 outputs
Outputs of similar age from BMC Bioinformatics
#16
of 42 outputs
Altmetric has tracked 14,162,573 research outputs across all sources so far. This one is in the 24th percentile – i.e., 24% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,343 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 22nd percentile – i.e., 22% 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 319,168 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.