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Network machine learning maps phytochemically rich “Hyperfoods” to fight COVID-19

Overview of attention for article published in Human Genomics, January 2021
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#10 of 564)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
1 news outlet
blogs
2 blogs
twitter
83 X users
reddit
1 Redditor

Citations

dimensions_citation
24 Dimensions

Readers on

mendeley
123 Mendeley
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Title
Network machine learning maps phytochemically rich “Hyperfoods” to fight COVID-19
Published in
Human Genomics, January 2021
DOI 10.1186/s40246-020-00297-x
Pubmed ID
Authors

Ivan Laponogov, Guadalupe Gonzalez, Madelen Shepherd, Ahad Qureshi, Dennis Veselkov, Georgia Charkoftaki, Vasilis Vasiliou, Jozef Youssef, Reza Mirnezami, Michael Bronstein, Kirill Veselkov

X Demographics

X Demographics

The data shown below were collected from the profiles of 83 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 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 123 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 14%
Researcher 15 12%
Student > Ph. D. Student 10 8%
Student > Doctoral Student 9 7%
Other 6 5%
Other 21 17%
Unknown 45 37%
Readers by discipline Count As %
Medicine and Dentistry 17 14%
Nursing and Health Professions 9 7%
Computer Science 9 7%
Pharmacology, Toxicology and Pharmaceutical Science 7 6%
Agricultural and Biological Sciences 7 6%
Other 26 21%
Unknown 48 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 64. 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 26 July 2022.
All research outputs
#664,072
of 25,387,668 outputs
Outputs from Human Genomics
#10
of 564 outputs
Outputs of similar age
#18,543
of 519,554 outputs
Outputs of similar age from Human Genomics
#2
of 17 outputs
Altmetric has tracked 25,387,668 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done particularly well, scoring higher than 98% 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 519,554 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 96% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.