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X Demographics
Mendeley readers
Attention Score in Context
| Title |
FASIMU: flexible software for flux-balance computation series in large metabolic networks
|
|---|---|
| Published in |
BMC Bioinformatics, January 2011
|
| DOI | 10.1186/1471-2105-12-28 |
| Pubmed ID | |
| Authors |
Andreas Hoppe, Sabrina Hoffmann, Andreas Gerasch, Christoph Gille, Hermann-Georg Holzhütter |
| Abstract |
Flux-balance analysis based on linear optimization is widely used to compute metabolic fluxes in large metabolic networks and gains increasingly importance in network curation and structural analysis. Thus, a computational tool flexible enough to realize a wide variety of FBA algorithms and able to handle batch series of flux-balance optimizations is of great benefit. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 154 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 3% |
| United Kingdom | 4 | 3% |
| Latvia | 3 | 2% |
| Colombia | 2 | 1% |
| Austria | 2 | 1% |
| Germany | 2 | 1% |
| Iran, Islamic Republic of | 2 | 1% |
| Czechia | 1 | <1% |
| Canada | 1 | <1% |
| Other | 4 | 3% |
| Unknown | 129 | 84% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 33 | 21% |
| Researcher | 33 | 21% |
| Student > Master | 27 | 18% |
| Professor > Associate Professor | 17 | 11% |
| Student > Bachelor | 9 | 6% |
| Other | 25 | 16% |
| Unknown | 10 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 88 | 57% |
| Computer Science | 20 | 13% |
| Biochemistry, Genetics and Molecular Biology | 13 | 8% |
| Engineering | 9 | 6% |
| Environmental Science | 2 | 1% |
| Other | 10 | 6% |
| Unknown | 12 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 01 March 2017.
All research outputs
#6,411,054
of 22,778,347 outputs
Outputs from BMC Bioinformatics
#2,470
of 7,276 outputs
Outputs of similar age
#47,164
of 182,533 outputs
Outputs of similar age from BMC Bioinformatics
#13
of 50 outputs
Altmetric has tracked 22,778,347 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 7,276 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 65% 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 182,533 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 50 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.