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X Demographics
Mendeley readers
Attention Score in Context
| Title |
In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development
|
|---|---|
| Published in |
Nature Communications, November 2016
|
| DOI | 10.1038/ncomms13427 |
| Pubmed ID | |
| Authors |
Ivan V. Ozerov, Ksenia V. Lezhnina, Evgeny Izumchenko, Artem V. Artemov, Sergey Medintsev, Quentin Vanhaelen, Alexander Aliper, Jan Vijg, Andreyan N. Osipov, Ivan Labat, Michael D. West, Anton Buzdin, Charles R. Cantor, Yuri Nikolsky, Nikolay Borisov, Irina Irincheeva, Edward Khokhlovich, David Sidransky, Miguel Luiz Camargo, Alex Zhavoronkov |
X Demographics
The data shown below were collected from the profiles of 30 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 | 4 | 13% |
| China | 1 | 3% |
| India | 1 | 3% |
| Switzerland | 1 | 3% |
| Austria | 1 | 3% |
| United Kingdom | 1 | 3% |
| Unknown | 21 | 70% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 27 | 90% |
| Scientists | 1 | 3% |
| 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 292 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 1% |
| Canada | 2 | <1% |
| Russia | 2 | <1% |
| Iran, Islamic Republic of | 1 | <1% |
| Colombia | 1 | <1% |
| United Kingdom | 1 | <1% |
| China | 1 | <1% |
| Unknown | 281 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 82 | 28% |
| Student > Ph. D. Student | 44 | 15% |
| Student > Master | 34 | 12% |
| Student > Bachelor | 23 | 8% |
| Other | 22 | 8% |
| Other | 36 | 12% |
| Unknown | 51 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 77 | 26% |
| Agricultural and Biological Sciences | 53 | 18% |
| Computer Science | 29 | 10% |
| Medicine and Dentistry | 18 | 6% |
| Pharmacology, Toxicology and Pharmaceutical Science | 13 | 4% |
| Other | 34 | 12% |
| Unknown | 68 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 342. 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 14 March 2024.
All research outputs
#97,460
of 25,837,817 outputs
Outputs from Nature Communications
#1,426
of 58,118 outputs
Outputs of similar age
#1,876
of 291,190 outputs
Outputs of similar age from Nature Communications
#29
of 874 outputs
Altmetric has tracked 25,837,817 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 58,118 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.5. This one has done particularly well, scoring higher than 97% 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 291,190 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 98% of its contemporaries.
We're also able to compare this research output to 874 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 96% of its contemporaries.