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X Demographics
Mendeley readers
Attention Score in Context
| Title |
EC2KEGG: a command line tool for comparison of metabolic pathways
|
|---|---|
| Published in |
Source Code for Biology and Medicine, September 2014
|
| DOI | 10.1186/1751-0473-9-19 |
| Pubmed ID | |
| Authors |
Aleksey Porollo |
| Abstract |
Next-generation sequencing and metagenome projects yield a large number of new genomes that need further annotations, such as identification of enzymes and metabolic pathways, or analysis of metabolic strategies of newly sequenced species in comparison to known organisms. While methods for enzyme identification are available, development of the command line tools for high-throughput comparative analysis and visualization of identified enzymes is lagging. |
X Demographics
The data shown below were collected from the profiles of 6 X users 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 | 17% |
| Japan | 1 | 17% |
| China | 1 | 17% |
| Canada | 1 | 17% |
| France | 1 | 17% |
| Unknown | 1 | 17% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 3 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | 2% |
| Malaysia | 1 | 2% |
| Netherlands | 1 | 2% |
| Czechia | 1 | 2% |
| Singapore | 1 | 2% |
| Unknown | 37 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 14 | 33% |
| Researcher | 11 | 26% |
| Student > Master | 4 | 10% |
| Student > Doctoral Student | 3 | 7% |
| Professor > Associate Professor | 3 | 7% |
| Other | 4 | 10% |
| Unknown | 3 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 21 | 50% |
| Biochemistry, Genetics and Molecular Biology | 11 | 26% |
| Computer Science | 3 | 7% |
| Environmental Science | 1 | 2% |
| Medicine and Dentistry | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 5 | 12% |
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 28 October 2014.
All research outputs
#7,477,223
of 23,498,099 outputs
Outputs from Source Code for Biology and Medicine
#41
of 127 outputs
Outputs of similar age
#74,050
of 238,897 outputs
Outputs of similar age from Source Code for Biology and Medicine
#2
of 4 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has gotten more attention than average, scoring higher than 67% 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 238,897 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 67% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.