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Clinical feature-related single-base substitution sequence signatures identified with an unsupervised machine learning approach

Overview of attention for article published in BMC Medical Genomics, December 2021
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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 (58th percentile)

Mentioned by

twitter
1 X user

Readers on

mendeley
2 Mendeley
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Title
Clinical feature-related single-base substitution sequence signatures identified with an unsupervised machine learning approach
Published in
BMC Medical Genomics, December 2021
DOI 10.1186/s12920-021-01144-1
Pubmed ID
Authors

Hongchen Ji, Junjie Li, Qiong Zhang, Jingyue Yang, Juanli Duan, Xiaowen Wang, Ben Ma, Zhuochao Zhang, Wei Pan, Hongmei Zhang

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 50%
Unknown 1 50%
Readers by discipline Count As %
Unknown 2 100%
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 21 December 2021.
All research outputs
#15,289,831
of 22,738,543 outputs
Outputs from BMC Medical Genomics
#675
of 1,218 outputs
Outputs of similar age
#274,789
of 495,273 outputs
Outputs of similar age from BMC Medical Genomics
#13
of 39 outputs
Altmetric has tracked 22,738,543 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,218 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 35th percentile – i.e., 35% 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 495,273 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 39 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 58% of its contemporaries.