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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Prediction of gene-phenotype associations in humans, mice, and plants using phenologs
|
|---|---|
| Published in |
BMC Bioinformatics, June 2013
|
| DOI | 10.1186/1471-2105-14-203 |
| Pubmed ID | |
| Authors |
John O Woods, Ulf Martin Singh-Blom, Jon M Laurent, Kriston L McGary, Edward M Marcotte |
| Abstract |
Phenotypes and diseases may be related to seemingly dissimilar phenotypes in other species by means of the orthology of underlying genes. Such "orthologous phenotypes," or "phenologs," are examples of deep homology, and may be used to predict additional candidate disease genes. |
X Demographics
The data shown below were collected from the profiles of 16 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 | 4 | 25% |
| Switzerland | 2 | 13% |
| Austria | 1 | 6% |
| India | 1 | 6% |
| Norway | 1 | 6% |
| Germany | 1 | 6% |
| Unknown | 6 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 50% |
| Scientists | 6 | 38% |
| Practitioners (doctors, other healthcare professionals) | 2 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 118 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 4% |
| Luxembourg | 2 | 2% |
| Brazil | 1 | <1% |
| India | 1 | <1% |
| Canada | 1 | <1% |
| Switzerland | 1 | <1% |
| Romania | 1 | <1% |
| Italy | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 103 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 35 | 30% |
| Student > Ph. D. Student | 30 | 25% |
| Student > Master | 12 | 10% |
| Student > Doctoral Student | 8 | 7% |
| Student > Bachelor | 8 | 7% |
| Other | 15 | 13% |
| Unknown | 10 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 50 | 42% |
| Biochemistry, Genetics and Molecular Biology | 19 | 16% |
| Computer Science | 15 | 13% |
| Medicine and Dentistry | 8 | 7% |
| Engineering | 4 | 3% |
| Other | 12 | 10% |
| Unknown | 10 | 8% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 December 2013.
All research outputs
#3,390,675
of 24,598,501 outputs
Outputs from BMC Bioinformatics
#1,115
of 7,559 outputs
Outputs of similar age
#28,428
of 201,513 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 89 outputs
Altmetric has tracked 24,598,501 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,559 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 85% 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 201,513 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 89 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.