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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Comparison and improvement of algorithms for computing minimal cut sets
|
|---|---|
| Published in |
BMC Bioinformatics, November 2013
|
| DOI | 10.1186/1471-2105-14-318 |
| Pubmed ID | |
| Authors |
Christian Jungreuthmayer, Govind Nair, Steffen Klamt, Jürgen Zanghellini |
| Abstract |
Constrained minimal cut sets (cMCSs) have recently been introduced as a framework to enumerate minimal genetic intervention strategies for targeted optimization of metabolic networks. Two different algorithmic schemes (adapted Berge algorithm and binary integer programming) have been proposed to compute cMCSs from elementary modes. However, in their original formulation both algorithms are not fully comparable. |
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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Iran, Islamic Republic of | 2 | 5% |
| Singapore | 1 | 3% |
| France | 1 | 3% |
| Belgium | 1 | 3% |
| United States | 1 | 3% |
| Unknown | 34 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 33% |
| Student > Ph. D. Student | 7 | 18% |
| Student > Master | 5 | 13% |
| Professor | 2 | 5% |
| Other | 2 | 5% |
| Other | 7 | 18% |
| Unknown | 4 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 23% |
| Biochemistry, Genetics and Molecular Biology | 7 | 18% |
| Computer Science | 7 | 18% |
| Mathematics | 5 | 13% |
| Engineering | 2 | 5% |
| Other | 3 | 8% |
| Unknown | 7 | 18% |
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 07 November 2013.
All research outputs
#18,353,475
of 22,729,647 outputs
Outputs from BMC Bioinformatics
#6,300
of 7,266 outputs
Outputs of similar age
#160,383
of 215,641 outputs
Outputs of similar age from BMC Bioinformatics
#95
of 120 outputs
Altmetric has tracked 22,729,647 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 7,266 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 5th percentile – i.e., 5% 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 215,641 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 120 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.