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X Demographics
Mendeley readers
Attention Score in Context
| Title |
KEGG spider: interpretation of genomics data in the context of the global gene metabolic network
|
|---|---|
| Published in |
Genome Biology, December 2008
|
| DOI | 10.1186/gb-2008-9-12-r179 |
| Pubmed ID | |
| Authors |
Alexey V Antonov, Sabine Dietmann, Hans W Mewes |
| Abstract |
KEGG spider is a web-based tool for interpretation of experimentally derived gene lists in order to gain understanding of metabolism variations at a genomic level. KEGG spider implements a 'pathway-free' framework that overcomes a major bottleneck of enrichment analyses: it provides global models uniting genes from different metabolic pathways. Analyzing a number of experimentally derived gene lists, we demonstrate that KEGG spider provides deeper insights into metabolism variations in comparison to existing methods. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 4% |
| United Kingdom | 4 | 3% |
| Germany | 3 | 3% |
| Netherlands | 1 | <1% |
| Sweden | 1 | <1% |
| France | 1 | <1% |
| China | 1 | <1% |
| Italy | 1 | <1% |
| Unknown | 102 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 39 | 33% |
| Student > Ph. D. Student | 28 | 24% |
| Professor > Associate Professor | 14 | 12% |
| Professor | 11 | 9% |
| Other | 4 | 3% |
| Other | 9 | 8% |
| Unknown | 14 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 63 | 53% |
| Biochemistry, Genetics and Molecular Biology | 17 | 14% |
| Computer Science | 11 | 9% |
| Medicine and Dentistry | 4 | 3% |
| Environmental Science | 2 | 2% |
| Other | 7 | 6% |
| Unknown | 15 | 13% |
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 17 March 2012.
All research outputs
#17,285,668
of 25,373,627 outputs
Outputs from Genome Biology
#4,093
of 4,467 outputs
Outputs of similar age
#153,984
of 181,062 outputs
Outputs of similar age from Genome Biology
#13
of 18 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. 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 181,062 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.