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Attention Score in Context
| Title |
Associations of SNPs located at candidate genes to bovine growth traits, prioritized with an interaction networks construction approach
|
|---|---|
| Published in |
BMC Genomic Data, July 2015
|
| DOI | 10.1186/s12863-015-0247-3 |
| Pubmed ID | |
| Authors |
Francisco Alejandro Paredes-Sánchez, Ana María Sifuentes-Rincón, Aldo Segura Cabrera, Carlos Armando García Pérez, Gaspar Manuel Parra Bracamonte, Pascuala Ambriz Morales |
| Abstract |
For most domestic animal species, including bovines, it is difficult to identify causative genetic variants involved in economically relevant traits. The candidate gene approach is efficient because it investigates genes that are expected to be associated with the expression of a trait and defines whether the genetic variation present in a population is associated with phenotypic diversity. A potential limitation of this approach is the identification of candidates. This study used a bioinformatics approach to identify candidate genes via a search guided by a functional interaction network. A functional interaction network tool, BosNet, was constructed for Bos taurus. Predictions for candidate genes were performed using the guilt-by-association principle in BosNet. Association analyses identified five novel markers within BosNet-prioritized genes that had significant effects on different growth traits in Charolais and Brahman cattle. BosNet is an excellent tool for the identification of single nucleotide polymorphisms that are potentially associated with complex traits. |
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 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 20% |
| Student > Master | 4 | 20% |
| Student > Doctoral Student | 2 | 10% |
| Student > Ph. D. Student | 2 | 10% |
| Professor | 1 | 5% |
| Other | 3 | 15% |
| Unknown | 4 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 45% |
| Biochemistry, Genetics and Molecular Biology | 3 | 15% |
| Veterinary Science and Veterinary Medicine | 2 | 10% |
| Medicine and Dentistry | 1 | 5% |
| Unknown | 5 | 25% |
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 07 September 2016.
All research outputs
#20,656,820
of 25,374,647 outputs
Outputs from BMC Genomic Data
#861
of 1,204 outputs
Outputs of similar age
#201,321
of 275,278 outputs
Outputs of similar age from BMC Genomic Data
#32
of 44 outputs
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So far Altmetric has tracked 1,204 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
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We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 18th percentile – i.e., 18% of its contemporaries scored the same or lower than it.