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Development of Simple and Accurate in Silico Ligand-Based Models for Predicting ABCG2 Inhibition

Overview of attention for article published in Frontiers in Chemistry, May 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

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2 X users

Citations

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2 Dimensions

Readers on

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3 Mendeley
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Title
Development of Simple and Accurate in Silico Ligand-Based Models for Predicting ABCG2 Inhibition
Published in
Frontiers in Chemistry, May 2022
DOI 10.3389/fchem.2022.863146
Pubmed ID
Authors

Shuheng Huang, Yingjie Gao, Xuelian Zhang, Ji Lu, Jun Wei, Hu Mei, Juan Xing, Xianchao Pan

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 1 33%
Unknown 2 67%
Readers by discipline Count As %
Chemistry 1 33%
Unknown 2 67%
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 07 June 2022.
All research outputs
#18,810,584
of 23,312,088 outputs
Outputs from Frontiers in Chemistry
#2,273
of 6,111 outputs
Outputs of similar age
#314,742
of 442,053 outputs
Outputs of similar age from Frontiers in Chemistry
#115
of 433 outputs
Altmetric has tracked 23,312,088 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 6,111 research outputs from this source. They receive a mean Attention Score of 2.1. This one has gotten more attention than average, scoring higher than 51% of its peers.
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 442,053 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 433 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 62% of its contemporaries.