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Attention Score in Context
Title |
Navigating the Multilayered Organization of Eukaryotic Signaling: A New Trend in Data Integration
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Published in |
PLoS Computational Biology, February 2014
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DOI | 10.1371/journal.pcbi.1003385 |
Pubmed ID | |
Authors |
Tapesh Santra, Walter Kolch, Boris N. Kholodenko |
Abstract |
The ever-increasing capacity of biological molecular data acquisition outpaces our ability to understand the meaningful relationships between molecules in a cell. Multiple databases were developed to store and organize these molecular data. However, emerging fundamental questions about concerted functions of these molecules in hierarchical cellular networks are poorly addressed. Here we review recent advances in the development of publically available databases that help us analyze the signal integration and processing by multilayered networks that specify biological responses in model organisms and human cells. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Norway | 1 | 17% |
United States | 1 | 17% |
Spain | 1 | 17% |
Peru | 1 | 17% |
Unknown | 2 | 33% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 3 | 50% |
Science communicators (journalists, bloggers, editors) | 2 | 33% |
Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Denmark | 3 | 4% |
United States | 2 | 3% |
Hungary | 1 | 1% |
Netherlands | 1 | 1% |
Brazil | 1 | 1% |
South Africa | 1 | 1% |
Portugal | 1 | 1% |
Czechia | 1 | 1% |
Germany | 1 | 1% |
Other | 2 | 3% |
Unknown | 65 | 82% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 24 | 30% |
Student > Ph. D. Student | 19 | 24% |
Professor | 6 | 8% |
Student > Bachelor | 5 | 6% |
Lecturer | 4 | 5% |
Other | 17 | 22% |
Unknown | 4 | 5% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 38 | 48% |
Biochemistry, Genetics and Molecular Biology | 17 | 22% |
Computer Science | 6 | 8% |
Engineering | 3 | 4% |
Chemistry | 3 | 4% |
Other | 6 | 8% |
Unknown | 6 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 05 March 2014.
All research outputs
#2,300,151
of 25,806,080 outputs
Outputs from PLoS Computational Biology
#2,026
of 9,043 outputs
Outputs of similar age
#26,666
of 331,938 outputs
Outputs of similar age from PLoS Computational Biology
#26
of 131 outputs
Altmetric has tracked 25,806,080 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,043 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done well, scoring higher than 77% 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 331,938 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 91% of its contemporaries.
We're also able to compare this research output to 131 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.