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Generative model based on junction tree variational autoencoder for HOMO value prediction and molecular optimization

Overview of attention for article published in Journal of Cheminformatics, February 2023
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  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
2 X users

Citations

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1 Dimensions

Readers on

mendeley
10 Mendeley
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Title
Generative model based on junction tree variational autoencoder for HOMO value prediction and molecular optimization
Published in
Journal of Cheminformatics, February 2023
DOI 10.1186/s13321-023-00681-4
Pubmed ID
Authors

Vladimir Kondratyev, Marian Dryzhakov, Timur Gimadiev, Dmitriy Slutskiy

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 30%
Student > Bachelor 1 10%
Researcher 1 10%
Unknown 5 50%
Readers by discipline Count As %
Chemistry 2 20%
Computer Science 1 10%
Biochemistry, Genetics and Molecular Biology 1 10%
Unknown 6 60%
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 November 2023.
All research outputs
#17,020,992
of 25,011,008 outputs
Outputs from Journal of Cheminformatics
#839
of 938 outputs
Outputs of similar age
#261,917
of 465,003 outputs
Outputs of similar age from Journal of Cheminformatics
#34
of 37 outputs
Altmetric has tracked 25,011,008 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 938 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one is in the 6th percentile – i.e., 6% 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 465,003 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.