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Chapter 7: Pharmacogenomics

Overview of attention for article published in PLoS Computational Biology, December 2012
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
49 news outlets
policy
1 policy source
twitter
21 X users
facebook
1 Facebook page
wikipedia
1 Wikipedia page
googleplus
2 Google+ users
pinterest
1 Pinner

Citations

dimensions_citation
55 Dimensions

Readers on

mendeley
375 Mendeley
citeulike
4 CiteULike
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Title
Chapter 7: Pharmacogenomics
Published in
PLoS Computational Biology, December 2012
DOI 10.1371/journal.pcbi.1002817
Pubmed ID
Authors

Konrad J. Karczewski, Roxana Daneshjou, Russ B. Altman

Abstract

There is great variation in drug-response phenotypes, and a "one size fits all" paradigm for drug delivery is flawed. Pharmacogenomics is the study of how human genetic information impacts drug response, and it aims to improve efficacy and reduced side effects. In this article, we provide an overview of pharmacogenetics, including pharmacokinetics (PK), pharmacodynamics (PD), gene and pathway interactions, and off-target effects. We describe methods for discovering genetic factors in drug response, including genome-wide association studies (GWAS), expression analysis, and other methods such as chemoinformatics and natural language processing (NLP). We cover the practical applications of pharmacogenomics both in the pharmaceutical industry and in a clinical setting. In drug discovery, pharmacogenomics can be used to aid lead identification, anticipate adverse events, and assist in drug repurposing efforts. Moreover, pharmacogenomic discoveries show promise as important elements of physician decision support. Finally, we consider the ethical, regulatory, and reimbursement challenges that remain for the clinical implementation of pharmacogenomics.

X Demographics

X Demographics

The data shown below were collected from the profiles of 21 X users 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 375 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 2%
Brazil 5 1%
United Kingdom 4 1%
Spain 4 1%
France 2 <1%
Ghana 1 <1%
Morocco 1 <1%
Germany 1 <1%
Canada 1 <1%
Other 3 <1%
Unknown 344 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 68 18%
Researcher 60 16%
Student > Bachelor 43 11%
Student > Master 40 11%
Professor > Associate Professor 24 6%
Other 78 21%
Unknown 62 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 90 24%
Medicine and Dentistry 58 15%
Biochemistry, Genetics and Molecular Biology 53 14%
Pharmacology, Toxicology and Pharmaceutical Science 39 10%
Computer Science 17 5%
Other 46 12%
Unknown 72 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 409. 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 14 April 2019.
All research outputs
#72,300
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#51
of 8,960 outputs
Outputs of similar age
#363
of 288,785 outputs
Outputs of similar age from PLoS Computational Biology
#2
of 121 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done particularly well, scoring higher than 99% of its peers.
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 288,785 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 121 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.