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X Demographics
Mendeley readers
Attention Score in Context
| Title |
TNA4OptFlux – a software tool for the analysis of strain optimization strategies
|
|---|---|
| Published in |
BMC Research Notes, May 2013
|
| DOI | 10.1186/1756-0500-6-175 |
| Pubmed ID | |
| Authors |
José P Pinto, Rui Pereira, João Cardoso, Isabel Rocha, Miguel Rocha |
| Abstract |
Rational approaches for Metabolic Engineering (ME) deal with the identification of modifications that improve the microbes' production capabilities of target compounds. One of the major challenges created by strain optimization algorithms used in these ME problems is the interpretation of the changes that lead to a given overproduction. Often, a single gene knockout induces changes in the fluxes of several reactions, as compared with the wild-type, and it is therefore difficult to evaluate the physiological differences of the in silico mutant. This is aggravated by the fact that genome-scale models per se are difficult to visualize, given the high number of reactions and metabolites involved. |
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 Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 4% |
| Unknown | 24 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 5 | 20% |
| Student > Ph. D. Student | 4 | 16% |
| Student > Master | 4 | 16% |
| Researcher | 3 | 12% |
| Professor | 2 | 8% |
| Other | 4 | 16% |
| Unknown | 3 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 28% |
| Computer Science | 4 | 16% |
| Biochemistry, Genetics and Molecular Biology | 4 | 16% |
| Engineering | 4 | 16% |
| Chemistry | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 4 | 16% |
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 28 May 2013.
All research outputs
#18,339,860
of 22,711,242 outputs
Outputs from BMC Research Notes
#3,009
of 4,257 outputs
Outputs of similar age
#144,931
of 192,813 outputs
Outputs of similar age from BMC Research Notes
#54
of 62 outputs
Altmetric has tracked 22,711,242 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,257 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 16th percentile – i.e., 16% 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 192,813 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.