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Salivary biomarker development using genomic, proteomic and metabolomic approaches

Overview of attention for article published in Genome Medicine, January 2012
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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 (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

Mentioned by

blogs
1 blog
twitter
2 tweeters
patent
1 patent

Citations

dimensions_citation
104 Dimensions

Readers on

mendeley
199 Mendeley
citeulike
1 CiteULike
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Title
Salivary biomarker development using genomic, proteomic and metabolomic approaches
Published in
Genome Medicine, January 2012
DOI 10.1186/gm383
Pubmed ID
Authors

Nicolai J Bonne, David TW Wong

Abstract

The use of saliva as a diagnostic sample provides a non-invasive, cost-efficient method of sample collection for disease screening without the need for highly trained professionals. Saliva collection is far more practical and safe compared with invasive methods of sample collection, because of the infection risk from contaminated needles during, for example, blood sampling. Furthermore, the use of saliva could increase the availability of accurate diagnostics for remote and impoverished regions. However, the development of salivary diagnostics has required technical innovation to allow stabilization and detection of analytes in the complex molecular mixture that is saliva. The recent development of cost-effective room temperature analyte stabilization methods, nucleic acid pre-amplification techniques and direct saliva transcriptomic analysis have allowed accurate detection and quantification of transcripts found in saliva. Novel protein stabilization methods have also facilitated improved proteomic analyses. Although candidate biomarkers have been discovered using epigenetic, transcriptomic, proteomic and metabolomic approaches, transcriptomic analyses have so far achieved the most progress in terms of sensitivity and specificity, and progress towards clinical implementation. Here, we review recent developments in salivary diagnostics that have been accomplished using genomic, transcriptomic, proteomic and metabolomic approaches.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 199 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Korea, Republic of 1 <1%
Netherlands 1 <1%
United Kingdom 1 <1%
India 1 <1%
Unknown 192 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 22%
Researcher 43 22%
Student > Bachelor 23 12%
Student > Master 22 11%
Student > Doctoral Student 12 6%
Other 25 13%
Unknown 31 16%
Readers by discipline Count As %
Medicine and Dentistry 44 22%
Agricultural and Biological Sciences 40 20%
Biochemistry, Genetics and Molecular Biology 32 16%
Chemistry 7 4%
Engineering 6 3%
Other 27 14%
Unknown 43 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 04 March 2020.
All research outputs
#1,769,011
of 17,136,794 outputs
Outputs from Genome Medicine
#434
of 1,141 outputs
Outputs of similar age
#15,536
of 159,942 outputs
Outputs of similar age from Genome Medicine
#8
of 20 outputs
Altmetric has tracked 17,136,794 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,141 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 23.4. This one has gotten more attention than average, scoring higher than 61% 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 159,942 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 90% of its contemporaries.
We're also able to compare this research output to 20 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.