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Mendeley readers
Attention Score in Context
| Title |
Ontology-based cross-species integration and analysis of Saccharomyces cerevisiae phenotypes
|
|---|---|
| Published in |
Journal of Biomedical Semantics, September 2012
|
| DOI | 10.1186/2041-1480-3-s2-s6 |
| Pubmed ID | |
| Authors |
Georgios V Gkoutos, Robert Hoehndorf |
| Abstract |
Ontologies are widely used in the biomedical community for annotation and integration of databases. Formal definitions can relate classes from different ontologies and thereby integrate data across different levels of granularity, domains and species. We have applied this methodology to the Ascomycete Phenotype Ontology (APO), enabling the reuse of various orthogonal ontologies and we have converted the phenotype associated data found in the SGD following our proposed patterns. We have integrated the resulting data in the cross-species phenotype network PhenomeNET, and we make both the cross-species integration of yeast phenotypes and a similarity-based comparison of yeast phenotypes across species available in the PhenomeBrowser. Furthermore, we utilize our definitions and the yeast phenotype annotations to suggest novel functional annotations of gene products in yeast. |
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 Kingdom | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 18% |
| Student > Master | 3 | 14% |
| Student > Ph. D. Student | 3 | 14% |
| Other | 2 | 9% |
| Student > Doctoral Student | 1 | 5% |
| Other | 5 | 23% |
| Unknown | 4 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 23% |
| Agricultural and Biological Sciences | 5 | 23% |
| Biochemistry, Genetics and Molecular Biology | 4 | 18% |
| Nursing and Health Professions | 2 | 9% |
| Medicine and Dentistry | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 4 | 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 21 October 2012.
All research outputs
#20,656,820
of 25,374,647 outputs
Outputs from Journal of Biomedical Semantics
#303
of 368 outputs
Outputs of similar age
#147,756
of 189,238 outputs
Outputs of similar age from Journal of Biomedical Semantics
#5
of 13 outputs
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So far Altmetric has tracked 368 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
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We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.