You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
BiGG: a Biochemical Genetic and Genomic knowledgebase of large scale metabolic reconstructions
|
|---|---|
| Published in |
BMC Bioinformatics, April 2010
|
| DOI | 10.1186/1471-2105-11-213 |
| Pubmed ID | |
| Authors |
Jan Schellenberger, Junyoung O Park, Tom M Conrad, Bernhard Ø Palsson |
| Abstract |
Genome-scale metabolic reconstructions under the Constraint Based Reconstruction and Analysis (COBRA) framework are valuable tools for analyzing the metabolic capabilities of organisms and interpreting experimental data. As the number of such reconstructions and analysis methods increases, there is a greater need for data uniformity and ease of distribution and use. |
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 % |
|---|---|---|
| United States | 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 659 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 21 | 3% |
| Germany | 10 | 2% |
| United Kingdom | 7 | 1% |
| Brazil | 6 | <1% |
| Spain | 5 | <1% |
| France | 5 | <1% |
| Latvia | 4 | <1% |
| Netherlands | 3 | <1% |
| Canada | 3 | <1% |
| Other | 27 | 4% |
| Unknown | 568 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 194 | 29% |
| Researcher | 142 | 22% |
| Student > Master | 89 | 14% |
| Student > Bachelor | 42 | 6% |
| Professor > Associate Professor | 30 | 5% |
| Other | 107 | 16% |
| Unknown | 55 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 279 | 42% |
| Biochemistry, Genetics and Molecular Biology | 112 | 17% |
| Computer Science | 55 | 8% |
| Engineering | 49 | 7% |
| Chemical Engineering | 16 | 2% |
| Other | 65 | 10% |
| Unknown | 83 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 13 June 2022.
All research outputs
#3,059,631
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#1,052
of 7,400 outputs
Outputs of similar age
#11,696
of 97,176 outputs
Outputs of similar age from BMC Bioinformatics
#8
of 70 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,400 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 done well, scoring higher than 85% 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 97,176 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 70 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.