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In silico comparative characterization of pharmacogenomic missense variants

Overview of attention for article published in BMC Genomics, May 2014
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Title
In silico comparative characterization of pharmacogenomic missense variants
Published in
BMC Genomics, May 2014
DOI 10.1186/1471-2164-15-s4-s4
Pubmed ID
Authors

Biao Li, Chet Seligman, Janita Thusberg, Jackson L Miller, Jim Auer, Michelle Whirl-Carrillo, Emidio Capriotti, Teri E Klein, Sean D Mooney

Abstract

Missense pharmacogenomic (PGx) variants refer to amino acid substitutions that potentially affect the pharmacokinetic (PK) or pharmacodynamic (PD) response to drug therapies. The PGx variants, as compared to disease-associated variants, have not been investigated as deeply. The ability to computationally predict future PGx variants is desirable; however, it is not clear what data sets should be used or what features are beneficial to this end. Hence we carried out a comparative characterization of PGx variants with annotated neutral and disease variants from UniProt, to test the predictive power of sequence conservation and structural information in discriminating these three groups.

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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.
Mendeley readers

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 %
Sri Lanka 1 5%
France 1 5%
Unknown 18 90%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 30%
Researcher 4 20%
Lecturer 2 10%
Student > Bachelor 2 10%
Professor 2 10%
Other 4 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 30%
Biochemistry, Genetics and Molecular Biology 5 25%
Medicine and Dentistry 4 20%
Nursing and Health Professions 2 10%
Pharmacology, Toxicology and Pharmaceutical Science 1 5%
Other 1 5%
Unknown 1 5%
Attention Score in Context

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 13 January 2015.
All research outputs
#15,315,142
of 22,778,347 outputs
Outputs from BMC Genomics
#6,684
of 10,643 outputs
Outputs of similar age
#132,716
of 226,332 outputs
Outputs of similar age from BMC Genomics
#103
of 197 outputs
Altmetric has tracked 22,778,347 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 10,643 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 29th percentile – i.e., 29% of its peers scored the same or lower than it.
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We're also able to compare this research output to 197 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.