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Identification of novel small molecule inhibitors for solute carrier SGLT1 using proteochemometric modeling

Overview of attention for article published in Journal of Cheminformatics, February 2019
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

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7 X users

Citations

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19 Dimensions

Readers on

mendeley
31 Mendeley
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Title
Identification of novel small molecule inhibitors for solute carrier SGLT1 using proteochemometric modeling
Published in
Journal of Cheminformatics, February 2019
DOI 10.1186/s13321-019-0337-8
Pubmed ID
Authors

Lindsey Burggraaff, Paul Oranje, Robin Gouka, Pieter van der Pijl, Marian Geldof, Herman W. T. van Vlijmen, Adriaan P. IJzerman, Gerard J. P. van Westen

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 26%
Student > Ph. D. Student 4 13%
Researcher 2 6%
Lecturer 1 3%
Student > Doctoral Student 1 3%
Other 4 13%
Unknown 11 35%
Readers by discipline Count As %
Chemistry 6 19%
Biochemistry, Genetics and Molecular Biology 4 13%
Pharmacology, Toxicology and Pharmaceutical Science 3 10%
Medicine and Dentistry 2 6%
Economics, Econometrics and Finance 1 3%
Other 2 6%
Unknown 13 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 28 February 2019.
All research outputs
#6,718,942
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#553
of 891 outputs
Outputs of similar age
#140,285
of 455,639 outputs
Outputs of similar age from Journal of Cheminformatics
#14
of 25 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one is in the 37th percentile – i.e., 37% 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 455,639 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 25 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.