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Convolutional neural network based on SMILES representation of compounds for detecting chemical motif

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 (91st percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
1 news outlet
twitter
21 X users
patent
1 patent

Citations

dimensions_citation
141 Dimensions

Readers on

mendeley
247 Mendeley
citeulike
1 CiteULike
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Title
Convolutional neural network based on SMILES representation of compounds for detecting chemical motif
Published in
BMC Bioinformatics, December 2018
DOI 10.1186/s12859-018-2523-5
Pubmed ID
Authors

Maya Hirohara, Yutaka Saito, Yuki Koda, Kengo Sato, Yasubumi Sakakibara

X Demographics

X Demographics

The data shown below were collected from the profiles of 21 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 247 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 247 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 40 16%
Student > Master 32 13%
Student > Bachelor 30 12%
Researcher 28 11%
Student > Doctoral Student 13 5%
Other 26 11%
Unknown 78 32%
Readers by discipline Count As %
Chemistry 45 18%
Computer Science 33 13%
Biochemistry, Genetics and Molecular Biology 21 9%
Engineering 17 7%
Chemical Engineering 10 4%
Other 36 15%
Unknown 85 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 22. 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 05 April 2021.
All research outputs
#1,655,601
of 25,079,481 outputs
Outputs from BMC Bioinformatics
#284
of 7,644 outputs
Outputs of similar age
#37,818
of 448,921 outputs
Outputs of similar age from BMC Bioinformatics
#10
of 216 outputs
Altmetric has tracked 25,079,481 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,644 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 96% 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 448,921 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 91% 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 95% of its contemporaries.