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Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques

Overview of attention for article published in BMC Bioinformatics, December 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
2 news outlets
twitter
16 X users

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
59 Mendeley
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Title
Computational prediction of plasma protein binding of cyclic peptides from small molecule experimental data using sparse modeling techniques
Published in
BMC Bioinformatics, December 2018
DOI 10.1186/s12859-018-2529-z
Pubmed ID
Authors

Takashi Tajimi, Naoki Wakui, Keisuke Yanagisawa, Yasushi Yoshikawa, Masahito Ohue, Yutaka Akiyama

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 14%
Student > Ph. D. Student 6 10%
Student > Bachelor 6 10%
Researcher 5 8%
Professor 4 7%
Other 13 22%
Unknown 17 29%
Readers by discipline Count As %
Computer Science 7 12%
Pharmacology, Toxicology and Pharmaceutical Science 6 10%
Biochemistry, Genetics and Molecular Biology 6 10%
Chemistry 5 8%
Social Sciences 3 5%
Other 13 22%
Unknown 19 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 25. 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 19 May 2021.
All research outputs
#1,457,006
of 24,647,023 outputs
Outputs from BMC Bioinformatics
#207
of 7,565 outputs
Outputs of similar age
#34,061
of 446,610 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 216 outputs
Altmetric has tracked 24,647,023 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,565 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 97% 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 446,610 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 216 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.