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Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients

Overview of attention for article published in Frontiers in Molecular Biosciences, October 2023
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Mentioned by

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1 X user

Citations

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3 Dimensions

Readers on

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2 Mendeley
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Title
Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 on metabolic unhealthy obese patients
Published in
Frontiers in Molecular Biosciences, October 2023
DOI 10.3389/fmolb.2023.1274463
Pubmed ID
Authors

Tengda Huang, Nan Jiang, Yujia Song, Hongyuan Pan, Ao Du, Bingxuan Yu, Xiaoquan Li, Jinyi He, Kefei Yuan, Zhen Wang

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

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 50%
Researcher 1 50%
Readers by discipline Count As %
Unspecified 1 50%
Biochemistry, Genetics and Molecular Biology 1 50%
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 09 October 2023.
All research outputs
#22,039,572
of 24,588,574 outputs
Outputs from Frontiers in Molecular Biosciences
#2,900
of 4,439 outputs
Outputs of similar age
#136,399
of 168,438 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#29
of 76 outputs
Altmetric has tracked 24,588,574 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,439 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% 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 168,438 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 76 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.