Report for: A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19

Title	A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19
Published in	PLoS Biology, November 2020
DOI	10.1371/journal.pbio.3000970
Pubmed ID	33156843
Authors	Yadi Zhou, Yuan Hou, Jiayu Shen, Reena Mehra, Asha Kallianpur, Daniel A. Culver, Michaela U. Gack, Samar Farha, Joe Zein, Suzy Comhair, Claudio Fiocchi, Thaddeus Stappenbeck, Timothy Chan, Charis Eng, Jae U. Jung, Lara Jehi, Serpil Erzurum, Feixiong Cheng

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Twitter Demographics

The data shown below were collected from the profiles of 346 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Geographical breakdown

Country	Count	As %
United States	87	25%
United Kingdom	12	3%
Spain	12	3%
Canada	10	3%
Japan	6	2%
India	4	1%
Mexico	4	1%
Germany	4	1%
Poland	4	1%
Other	35	10%
Unknown	168	49%

Demographic breakdown

Type	Count	As %
Members of the public	275	79%
Practitioners (doctors, other healthcare professionals)	36	10%
Scientists	26	8%
Science communicators (journalists, bloggers, editors)	9	3%

Mendeley readers

The data shown below were compiled from readership statistics for 276 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country	Count	As %
Unknown	276	100%

Demographic breakdown

Readers by professional status	Count	As %
Researcher	41	15%
Student > Ph. D. Student	30	11%
Student > Master	28	10%
Student > Bachelor	23	8%
Other	13	5%
Other	58	21%
Unknown	83	30%

Readers by discipline	Count	As %
Medicine and Dentistry	55	20%
Biochemistry, Genetics and Molecular Biology	23	8%
Computer Science	15	5%
Pharmacology, Toxicology and Pharmaceutical Science	15	5%
Nursing and Health Professions	14	5%
Other	55	20%
Unknown	99	36%

Attention Score in Context

This research output has an Altmetric Attention Score of 1038. 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 25 April 2023.

All research outputs

#13,482

of 23,965,413 outputs

Outputs from PLoS Biology

#42

of 7,188 outputs

Outputs of similar age

#635

of 423,488 outputs

Outputs of similar age from PLoS Biology

of 121 outputs

Altmetric has tracked 23,965,413 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.

So far Altmetric has tracked 7,188 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 53.5. This one has done particularly well, scoring higher than 99% 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 423,488 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 99% of its contemporaries.

We're also able to compare this research output to 121 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.

A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19

About this Attention Score

Mentioned by

Citations

Readers on

Twitter Demographics

Geographical breakdown

Demographic breakdown

Mendeley readers

Geographical breakdown

Demographic breakdown

Attention Score in Context