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Mendeley readers
Attention Score in Context
| Title |
Genome-scale metabolic model of the fission yeast Schizosaccharomyces pombe and the reconciliation of in silico/in vivo mutant growth
|
|---|---|
| Published in |
BMC Systems Biology, July 2012
|
| DOI | 10.1186/1752-0509-6-49 |
| Pubmed ID | |
| Authors |
Seung Bum Sohn, Tae Yong Kim, Jay H Lee, Sang Yup Lee |
| Abstract |
Over the last decade, the genome-scale metabolic models have been playing increasingly important roles in elucidating metabolic characteristics of biological systems for a wide range of applications including, but not limited to, system-wide identification of drug targets and production of high value biochemical compounds. However, these genome-scale metabolic models must be able to first predict known in vivo phenotypes before it is applied towards these applications with high confidence. One benchmark for measuring the in silico capability in predicting in vivo phenotypes is the use of single-gene mutant libraries to measure the accuracy of knockout simulations in predicting mutant growth phenotypes. |
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 % |
|---|---|---|
| Japan | 1 | 1% |
| United States | 1 | 1% |
| Singapore | 1 | 1% |
| Unknown | 78 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 27% |
| Student > Ph. D. Student | 15 | 19% |
| Student > Bachelor | 9 | 11% |
| Student > Doctoral Student | 7 | 9% |
| Student > Postgraduate | 6 | 7% |
| Other | 14 | 17% |
| Unknown | 8 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 35 | 43% |
| Biochemistry, Genetics and Molecular Biology | 15 | 19% |
| Engineering | 5 | 6% |
| Computer Science | 4 | 5% |
| Chemistry | 3 | 4% |
| Other | 9 | 11% |
| Unknown | 10 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 January 2023.
All research outputs
#7,680,750
of 23,373,475 outputs
Outputs from BMC Systems Biology
#314
of 1,143 outputs
Outputs of similar age
#55,522
of 165,426 outputs
Outputs of similar age from BMC Systems Biology
#12
of 34 outputs
Altmetric has tracked 23,373,475 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,143 research outputs from this source. They receive a mean Attention Score of 3.6. This one has gotten more attention than average, scoring higher than 63% 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 165,426 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 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 64% of its contemporaries.