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X Demographics
Mendeley readers
Attention Score in Context
Title |
Chapter 5: Network Biology Approach to Complex Diseases
|
---|---|
Published in |
PLoS Computational Biology, December 2012
|
DOI | 10.1371/journal.pcbi.1002820 |
Pubmed ID | |
Authors |
Dong-Yeon Cho, Yoo-Ah Kim, Teresa M. Przytycka |
X Demographics
The data shown below were collected from the profiles of 33 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 24% |
France | 2 | 6% |
Australia | 2 | 6% |
Canada | 1 | 3% |
Germany | 1 | 3% |
Netherlands | 1 | 3% |
Japan | 1 | 3% |
Indonesia | 1 | 3% |
United Kingdom | 1 | 3% |
Other | 1 | 3% |
Unknown | 14 | 42% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 16 | 48% |
Members of the public | 15 | 45% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 523 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 10 | 2% |
United Kingdom | 6 | 1% |
Germany | 3 | <1% |
France | 3 | <1% |
India | 3 | <1% |
Norway | 2 | <1% |
Brazil | 2 | <1% |
Sweden | 2 | <1% |
Spain | 2 | <1% |
Other | 10 | 2% |
Unknown | 480 | 92% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 153 | 29% |
Researcher | 121 | 23% |
Student > Master | 52 | 10% |
Professor > Associate Professor | 34 | 7% |
Student > Bachelor | 24 | 5% |
Other | 92 | 18% |
Unknown | 47 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 188 | 36% |
Biochemistry, Genetics and Molecular Biology | 93 | 18% |
Computer Science | 67 | 13% |
Medicine and Dentistry | 34 | 7% |
Engineering | 21 | 4% |
Other | 54 | 10% |
Unknown | 66 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 21. 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 29 May 2017.
All research outputs
#1,859,515
of 25,884,216 outputs
Outputs from PLoS Computational Biology
#1,598
of 9,065 outputs
Outputs of similar age
#16,478
of 291,431 outputs
Outputs of similar age from PLoS Computational Biology
#19
of 120 outputs
Altmetric has tracked 25,884,216 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,065 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.3. This one has done well, scoring higher than 82% 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 291,431 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 94% of its contemporaries.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.