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Mendeley readers
Attention Score in Context
Title |
Robust flux balance analysis of multiscale biochemical reaction networks
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Published in |
BMC Bioinformatics, July 2013
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DOI | 10.1186/1471-2105-14-240 |
Pubmed ID | |
Authors |
Yuekai Sun, Ronan MT Fleming, Ines Thiele, Michael A Saunders |
Abstract |
Biological processes such as metabolism, signaling, and macromolecular synthesis can be modeled as large networks of biochemical reactions. Large and comprehensive networks, like integrated networks that represent metabolism and macromolecular synthesis, are inherently multiscale because reaction rates can vary over many orders of magnitude. They require special methods for accurate analysis because naive use of standard optimization systems can produce inaccurate or erroneously infeasible results. |
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 % |
---|---|---|
United States | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 50% |
Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 6% |
Portugal | 1 | 1% |
Chile | 1 | 1% |
Brazil | 1 | 1% |
South Africa | 1 | 1% |
Germany | 1 | 1% |
Belgium | 1 | 1% |
Singapore | 1 | 1% |
Russia | 1 | 1% |
Other | 1 | 1% |
Unknown | 70 | 83% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 24 | 29% |
Student > Ph. D. Student | 23 | 27% |
Student > Master | 10 | 12% |
Student > Bachelor | 6 | 7% |
Professor | 6 | 7% |
Other | 13 | 15% |
Unknown | 2 | 2% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 36 | 43% |
Computer Science | 14 | 17% |
Biochemistry, Genetics and Molecular Biology | 11 | 13% |
Engineering | 7 | 8% |
Medicine and Dentistry | 4 | 5% |
Other | 6 | 7% |
Unknown | 6 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 23 May 2014.
All research outputs
#14,172,739
of 22,715,151 outputs
Outputs from BMC Bioinformatics
#4,719
of 7,260 outputs
Outputs of similar age
#111,479
of 198,188 outputs
Outputs of similar age from BMC Bioinformatics
#56
of 84 outputs
Altmetric has tracked 22,715,151 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,260 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 30th percentile – i.e., 30% 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 198,188 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.