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Mendeley readers
Attention Score in Context
| Title |
Pharmacogenomic assessment of Mexican and Peruvian populations
|
|---|---|
| Published in |
Pharmacogenomics, April 2015
|
| DOI | 10.2217/pgs.15.10 |
| Pubmed ID | |
| Authors |
Sharon Marsh, Cristi R King, Derek J Van Booven, Jane Y Revollo, Robert H Gilman, Howard L McLeod |
| Abstract |
Clinically relevant polymorphisms often demonstrate population-specific allele frequencies. Central and South America remain largely uncategorized in the context of pharmacogenomics. We assessed 15 polymorphisms from 12 genes (ABCB1 3435C>T, ABCG2 Q141K, CYP1B1*3, CYP2C19*2, CYP3A4*1B, CYP3A5*3C, ERCC1 N118N, ERCC2 K751Q, GSTP1 I105V, TPMT 238G>C, TPMT 460G>A, TPMT 719A>G, TYMS TSER, UGT1A1*28 and UGT1A1 -3156G>A) in 81 Peruvian and 95 Mexican individuals. Six polymorphism frequencies differed significantly between the two populations: ABCB1 3435C>T, CYP1B1*3, GSTP1 I105V, TPMT 460G>A, UGT1A1*28 and UGT1A1 -3156G>A. The pattern of observed allele frequencies for all polymorphisms could not be accurately estimated from any single previously studied population. This highlights the need to expand the scope of geographic data for use in pharmacogenomics studies. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 44 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 8 | 18% |
| Student > Ph. D. Student | 8 | 18% |
| Researcher | 7 | 16% |
| Student > Doctoral Student | 4 | 9% |
| Student > Master | 3 | 7% |
| Other | 4 | 9% |
| Unknown | 10 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 12 | 27% |
| Agricultural and Biological Sciences | 7 | 16% |
| Biochemistry, Genetics and Molecular Biology | 5 | 11% |
| Medicine and Dentistry | 5 | 11% |
| Chemistry | 2 | 5% |
| Other | 3 | 7% |
| Unknown | 10 | 23% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 22 June 2015.
All research outputs
#13,746,181
of 22,813,792 outputs
Outputs from Pharmacogenomics
#611
of 1,100 outputs
Outputs of similar age
#132,482
of 264,602 outputs
Outputs of similar age from Pharmacogenomics
#13
of 23 outputs
Altmetric has tracked 22,813,792 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,100 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
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 264,602 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.