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A novel method for inference of acyclic chemical compounds with bounded branch-height based on artificial neural networks and integer programming

Overview of attention for article published in Algorithms for Molecular Biology, August 2021
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 X user

Citations

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10 Dimensions

Readers on

mendeley
4 Mendeley
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Title
A novel method for inference of acyclic chemical compounds with bounded branch-height based on artificial neural networks and integer programming
Published in
Algorithms for Molecular Biology, August 2021
DOI 10.1186/s13015-021-00197-2
Pubmed ID
Authors

Naveed Ahmed Azam, Jianshen Zhu, Yanming Sun, Yu Shi, Aleksandar Shurbevski, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu

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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 50%
Professor 1 25%
Unknown 1 25%
Readers by discipline Count As %
Chemistry 2 50%
Materials Science 1 25%
Unknown 1 25%
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 16 August 2021.
All research outputs
#15,708,425
of 23,344,526 outputs
Outputs from Algorithms for Molecular Biology
#148
of 264 outputs
Outputs of similar age
#249,769
of 431,060 outputs
Outputs of similar age from Algorithms for Molecular Biology
#5
of 8 outputs
Altmetric has tracked 23,344,526 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 264 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 34th percentile – i.e., 34% 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 431,060 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.