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Pharmacometabolomics Informs Viromics toward Precision Medicine

Overview of attention for article published in Frontiers in Pharmacology, October 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
2 X users

Readers on

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44 Mendeley
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Title
Pharmacometabolomics Informs Viromics toward Precision Medicine
Published in
Frontiers in Pharmacology, October 2016
DOI 10.3389/fphar.2016.00411
Pubmed ID
Authors

Angeliki Balasopoulou, George P. Patrinos, Theodora Katsila

Abstract

Nowadays, we are experiencing the big data era with the emerging challenge of single data interpretation. Although the advent of high-throughput technologies as well as chemo- and bio-informatics tools presents pan-omics data as the way forward to precision medicine, personalized health care and tailored-made therapeutics can be only envisaged when interindividual variability in response to/toxicity of xenobiotics can be interpreted and thus, predicted. We know that such variability is the net outcome of genetics (host and microbiota) and environmental factors (diet, lifestyle, polypharmacy, and microbiota) and for this, tremendous efforts have been made to clarify key-molecules from correlation to causality to clinical significance. Herein, we focus on the host-microbiome interplay and its direct and indirect impact on efficacy and toxicity of xenobiotics and we inevitably wonder about the role of viruses, as the least acknowledged ones. We present the emerging discipline of pharmacometabolomics-informed viromics, in which pre-dose metabotypes can assist modeling and prediction of interindividual response to/toxicity of xenobiotics. Such features, either alone or in combination with host genetics, can power biomarker discovery so long as the features are variable among patients, stable enough to be of predictive value, and better than pre-existing tools for predicting therapeutic efficacy/toxicity.

X Demographics

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.
Mendeley readers

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 %
Brazil 2 5%
Unknown 42 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 20%
Student > Master 7 16%
Student > Ph. D. Student 6 14%
Student > Doctoral Student 5 11%
Student > Bachelor 4 9%
Other 6 14%
Unknown 7 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 27%
Agricultural and Biological Sciences 5 11%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Computer Science 3 7%
Engineering 3 7%
Other 9 20%
Unknown 9 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 09 October 2023.
All research outputs
#2,277,860
of 24,584,609 outputs
Outputs from Frontiers in Pharmacology
#919
of 18,606 outputs
Outputs of similar age
#39,250
of 319,834 outputs
Outputs of similar age from Frontiers in Pharmacology
#19
of 163 outputs
Altmetric has tracked 24,584,609 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 18,606 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has done particularly well, scoring higher than 95% 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 319,834 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 87% of its contemporaries.
We're also able to compare this research output to 163 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.