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Accelerating bioinformatics research with International Conference on Intelligent Biology and Medicine 2020

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

twitter
3 X users

Citations

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1 Dimensions

Readers on

mendeley
24 Mendeley
Title
Accelerating bioinformatics research with International Conference on Intelligent Biology and Medicine 2020
Published in
BMC Bioinformatics, December 2020
DOI 10.1186/s12859-020-03890-y
Pubmed ID
Authors

Yan Guo, Li Shen, Xinghua Shi, Kai Wang, Yulin Dai, Zhongming Zhao

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 21%
Student > Bachelor 3 13%
Other 2 8%
Librarian 2 8%
Student > Master 2 8%
Other 3 13%
Unknown 7 29%
Readers by discipline Count As %
Medicine and Dentistry 7 29%
Nursing and Health Professions 4 17%
Mathematics 2 8%
Agricultural and Biological Sciences 1 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Other 2 8%
Unknown 7 29%
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 29 December 2020.
All research outputs
#18,115,398
of 23,270,775 outputs
Outputs from BMC Bioinformatics
#6,025
of 7,368 outputs
Outputs of similar age
#355,572
of 502,851 outputs
Outputs of similar age from BMC Bioinformatics
#135
of 148 outputs
Altmetric has tracked 23,270,775 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,368 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 13th percentile – i.e., 13% 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 502,851 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 148 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.