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Using omics approaches to understand pulmonary diseases

Overview of attention for article published in Respiratory Research, August 2017
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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 (86th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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25 X users
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1 Google+ user
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Citations

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91 Dimensions

Readers on

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174 Mendeley
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Title
Using omics approaches to understand pulmonary diseases
Published in
Respiratory Research, August 2017
DOI 10.1186/s12931-017-0631-9
Pubmed ID
Authors

Mengyuan Kan, Maya Shumyatcher, Blanca E. Himes

Abstract

Omics approaches are high-throughput unbiased technologies that provide snapshots of various aspects of biological systems and include: 1) genomics, the measure of DNA variation; 2) transcriptomics, the measure of RNA expression; 3) epigenomics, the measure of DNA alterations not involving sequence variation that influence RNA expression; 4) proteomics, the measure of protein expression or its chemical modifications; and 5) metabolomics, the measure of metabolite levels. Our understanding of pulmonary diseases has increased as a result of applying these omics approaches to characterize patients, uncover mechanisms underlying drug responsiveness, and identify effects of environmental exposures and interventions. As more tissue- and cell-specific omics data is analyzed and integrated for diverse patients under various conditions, there will be increased identification of key mechanisms that underlie pulmonary biological processes, disease endotypes, and novel therapeutics that are efficacious in select individuals. We provide a synopsis of how omics approaches have advanced our understanding of asthma, chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), idiopathic pulmonary fibrosis (IPF), and pulmonary arterial hypertension (PAH), and we highlight ongoing work that will facilitate pulmonary disease precision medicine.

X Demographics

X Demographics

The data shown below were collected from the profiles of 25 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 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 174 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 17%
Researcher 27 16%
Student > Bachelor 18 10%
Other 12 7%
Professor > Associate Professor 12 7%
Other 33 19%
Unknown 43 25%
Readers by discipline Count As %
Medicine and Dentistry 46 26%
Biochemistry, Genetics and Molecular Biology 27 16%
Agricultural and Biological Sciences 18 10%
Immunology and Microbiology 5 3%
Pharmacology, Toxicology and Pharmaceutical Science 5 3%
Other 23 13%
Unknown 50 29%
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 April 2021.
All research outputs
#2,407,387
of 25,394,764 outputs
Outputs from Respiratory Research
#244
of 3,064 outputs
Outputs of similar age
#44,281
of 327,325 outputs
Outputs of similar age from Respiratory Research
#10
of 53 outputs
Altmetric has tracked 25,394,764 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 3,064 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has done particularly well, scoring higher than 91% 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 327,325 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 86% of its contemporaries.
We're also able to compare this research output to 53 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.