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Mendeley readers
Attention Score in Context
| Title |
Mining phenotypes for gene function prediction
|
|---|---|
| Published in |
BMC Bioinformatics, March 2008
|
| DOI | 10.1186/1471-2105-9-136 |
| Pubmed ID | |
| Authors |
Philip Groth, Bertram Weiss, Hans-Dieter Pohlenz, Ulf Leser |
| Abstract |
Health and disease of organisms are reflected in their phenotypes. Often, a genetic component to a disease is discovered only after clearly defining its phenotype. In the past years, many technologies to systematically generate phenotypes in a high-throughput manner, such as RNA interference or gene knock-out, have been developed and used to decipher functions for genes. However, there have been relatively few efforts to make use of phenotype data beyond the single genotype-phenotype relationships. |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 6 | 9% |
| Japan | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 61 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 30% |
| Student > Ph. D. Student | 15 | 22% |
| Professor > Associate Professor | 7 | 10% |
| Student > Master | 7 | 10% |
| Student > Doctoral Student | 3 | 4% |
| Other | 8 | 12% |
| Unknown | 8 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 29 | 42% |
| Computer Science | 12 | 17% |
| Biochemistry, Genetics and Molecular Biology | 8 | 12% |
| Medicine and Dentistry | 6 | 9% |
| Engineering | 2 | 3% |
| Other | 1 | 1% |
| Unknown | 11 | 16% |
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 08 November 2016.
All research outputs
#7,454,951
of 22,790,780 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,280 outputs
Outputs of similar age
#28,389
of 79,803 outputs
Outputs of similar age from BMC Bioinformatics
#17
of 45 outputs
Altmetric has tracked 22,790,780 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 7,280 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% 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 79,803 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.