| Title |
Exploring public genomics data for population pharmacogenomics
|
|---|---|
| Published in |
PLOS ONE, August 2017
|
| DOI | 10.1371/journal.pone.0182138 |
| Pubmed ID | |
| Authors |
Kleanthi Lakiotaki, Alexandros Kanterakis, Evgenia Kartsaki, Theodora Katsila, George P. Patrinos, George Potamias |
| Abstract |
Racial and ethnic differences in drug responses are now well studied and documented. Pharmacogenomics research seeks to unravel the genetic underpinnings of inter-individual variability with the aim of tailored-made theranostics and therapeutics. Taking into account the differential expression of pharmacogenes coding for key metabolic enzymes and transporters that affect drug pharmacokinetics and pharmacodynamics, we advise that data interpretation and analysis need to occur in light of geographical ancestry, if implications for drug development and global health are to be considered. Herein, we exploit ePGA, a web-based electronic Pharmacogenomics Assistant and publicly available genetic data from the 1000 Genomes Project to explore genotype to phenotype associations among the 1000 Genomes Project populations. |
X Demographics
The data shown below were collected from the profiles of 5 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 Kingdom | 1 | 20% |
| Greece | 1 | 20% |
| Unknown | 3 | 60% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 93 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 17% |
| Student > Master | 8 | 9% |
| Student > Bachelor | 7 | 8% |
| Researcher | 7 | 8% |
| Other | 6 | 6% |
| Other | 8 | 9% |
| Unknown | 41 | 44% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 23 | 25% |
| Pharmacology, Toxicology and Pharmaceutical Science | 8 | 9% |
| Agricultural and Biological Sciences | 7 | 8% |
| Computer Science | 6 | 6% |
| Medicine and Dentistry | 2 | 2% |
| Other | 6 | 6% |
| Unknown | 41 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 23 May 2022.
All research outputs
#4,667,846
of 23,498,099 outputs
Outputs from PLOS ONE
#67,505
of 201,220 outputs
Outputs of similar age
#80,181
of 318,558 outputs
Outputs of similar age from PLOS ONE
#1,114
of 4,111 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 201,220 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.3. This one has gotten more attention than average, scoring higher than 66% of its peers.
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We're also able to compare this research output to 4,111 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.