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Mendeley readers
Attention Score in Context
| Title |
Pharmacogenetics in type 2 diabetes: potential implications for clinical practice
|
|---|---|
| Published in |
Genome Medicine, November 2011
|
| DOI | 10.1186/gm292 |
| Pubmed ID | |
| Authors |
Chunmei Huang, Jose C Florez |
| Abstract |
Pharmacogenetic research aims to study how genetic variation may influence drug efficacy and/or toxicity; pharmacogenomics expands this quest to the entire genome. Pharmacogenetic findings may help to uncover new drug targets, illuminate pathophysiology, clarify disease heterogeneity, aid in the fine-mapping of genetic associations, and contribute to personalized treatment. In diabetes, there is precedent for the successful application of pharmacogenetic concepts to monogenic forms of the disease, such as maturity onset diabetes of the young or neonatal diabetes. Whether similar insights will be produced for the common form of type 2 diabetes remains to be seen. With recent advances in genetic approaches, the successive application of candidate gene studies, large-scale genotyping studies and genome-wide association studies has begun to generate suggestive results that may lead to changes in clinical practice. However, many potential barriers to the translation of pharmacogenetic discoveries to the clinical management of diabetes still remain. Here, we offer a contemporary overview of the field in its current state, identify potential obstacles, and highlight future directions. |
Mendeley readers
The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 2% |
| Unknown | 50 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 11 | 22% |
| Researcher | 7 | 14% |
| Other | 6 | 12% |
| Student > Bachelor | 5 | 10% |
| Student > Ph. D. Student | 4 | 8% |
| Other | 9 | 18% |
| Unknown | 9 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 12 | 24% |
| Agricultural and Biological Sciences | 11 | 22% |
| Biochemistry, Genetics and Molecular Biology | 5 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 4 | 8% |
| Environmental Science | 1 | 2% |
| Other | 4 | 8% |
| Unknown | 14 | 27% |
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 08 December 2011.
All research outputs
#5,422,599
of 25,371,288 outputs
Outputs from Genome Medicine
#995
of 1,585 outputs
Outputs of similar age
#42,205
of 246,421 outputs
Outputs of similar age from Genome Medicine
#9
of 18 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,585 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.8. This one is in the 35th percentile – i.e., 35% 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 246,421 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 82% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.