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Non-parametric synergy modeling of chemical compounds with Gaussian processes

Overview of attention for article published in BMC Bioinformatics, January 2022
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2 X users

Citations

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3 Dimensions

Readers on

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11 Mendeley
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Title
Non-parametric synergy modeling of chemical compounds with Gaussian processes
Published in
BMC Bioinformatics, January 2022
DOI 10.1186/s12859-021-04508-7
Pubmed ID
Authors

Yuliya Shapovalova, Tom Heskes, Tjeerd Dijkstra

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

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 18%
Student > Doctoral Student 1 9%
Student > Ph. D. Student 1 9%
Unspecified 1 9%
Student > Bachelor 1 9%
Other 1 9%
Unknown 4 36%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 18%
Pharmacology, Toxicology and Pharmaceutical Science 2 18%
Unspecified 1 9%
Computer Science 1 9%
Medicine and Dentistry 1 9%
Other 0 0%
Unknown 4 36%
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 07 January 2022.
All research outputs
#18,171,423
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#6,065
of 7,388 outputs
Outputs of similar age
#345,900
of 509,221 outputs
Outputs of similar age from BMC Bioinformatics
#133
of 145 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,388 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 12th percentile – i.e., 12% 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 509,221 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 145 others from the same source and published within six weeks on either side of this one. This one is in the 2nd percentile – i.e., 2% of its contemporaries scored the same or lower than it.