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Mendeley readers
Attention Score in Context
Title |
Effects of protein interaction data integration, representation and reliability on the use of network properties for drug target prediction
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Published in |
BMC Bioinformatics, November 2012
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DOI | 10.1186/1471-2105-13-294 |
Pubmed ID | |
Authors |
Antonio Mora, Ian M Donaldson |
Abstract |
Previous studies have noted that drug targets appear to be associated with higher-degree or higher-centrality proteins in interaction networks. These studies explicitly or tacitly make choices of different source databases, data integration strategies, representation of proteins and complexes, and data reliability assumptions. Here we examined how the use of different data integration and representation techniques, or different notions of reliability, may affect the efficacy of degree and centrality as features in drug target prediction. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Peru | 1 | 50% |
United Kingdom | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Science communicators (journalists, bloggers, editors) | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 4% |
Italy | 2 | 2% |
United States | 2 | 2% |
France | 2 | 2% |
Netherlands | 1 | 1% |
Turkey | 1 | 1% |
Hungary | 1 | 1% |
Brazil | 1 | 1% |
Portugal | 1 | 1% |
Other | 2 | 2% |
Unknown | 65 | 80% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 25 | 31% |
Student > Ph. D. Student | 18 | 22% |
Student > Master | 8 | 10% |
Student > Postgraduate | 7 | 9% |
Student > Doctoral Student | 6 | 7% |
Other | 12 | 15% |
Unknown | 5 | 6% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 28 | 35% |
Computer Science | 21 | 26% |
Biochemistry, Genetics and Molecular Biology | 8 | 10% |
Medicine and Dentistry | 7 | 9% |
Engineering | 2 | 2% |
Other | 6 | 7% |
Unknown | 9 | 11% |
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 26 November 2012.
All research outputs
#15,708,425
of 23,344,526 outputs
Outputs from BMC Bioinformatics
#5,490
of 7,387 outputs
Outputs of similar age
#114,695
of 181,271 outputs
Outputs of similar age from BMC Bioinformatics
#73
of 108 outputs
Altmetric has tracked 23,344,526 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,387 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 17th percentile – i.e., 17% 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 181,271 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 108 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.