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GODoc: high-throughput protein function prediction using novel k-nearest-neighbor and voting algorithms

Overview of attention for article published in BMC Bioinformatics, November 2020
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Mentioned by

twitter
2 tweeters

Readers on

mendeley
6 Mendeley
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Title
GODoc: high-throughput protein function prediction using novel k-nearest-neighbor and voting algorithms
Published in
BMC Bioinformatics, November 2020
DOI 10.1186/s12859-020-03556-9
Pubmed ID
Authors

Yi-Wei Liu, Tz-Wei Hsu, Che-Yu Chang, Wen-Hung Liao, Jia-Ming Chang

Twitter Demographics

The data shown below were collected from the profiles of 2 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 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 33%
Other 2 33%
Student > Master 1 17%
Unknown 1 17%
Readers by discipline Count As %
Computer Science 3 50%
Agricultural and Biological Sciences 1 17%
Unknown 2 33%

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 November 2020.
All research outputs
#15,603,037
of 19,458,329 outputs
Outputs from BMC Bioinformatics
#5,682
of 6,599 outputs
Outputs of similar age
#343,616
of 466,820 outputs
Outputs of similar age from BMC Bioinformatics
#438
of 480 outputs
Altmetric has tracked 19,458,329 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 6,599 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 6th percentile – i.e., 6% 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 466,820 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 480 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.