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Clinical veterinary proteomics: Techniques and approaches to decipher the animal plasma proteome

Overview of attention for article published in Veterinary Journal, November 2017
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  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

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Title
Clinical veterinary proteomics: Techniques and approaches to decipher the animal plasma proteome
Published in
Veterinary Journal, November 2017
DOI 10.1016/j.tvjl.2017.10.022
Pubmed ID
Authors

P. Ghodasara, P. Sadowski, N. Satake, S. Kopp, P.C. Mills

Abstract

Over the last two decades, technological advancements in the field of proteomics have advanced our understanding of the complex biological systems of living organisms. Techniques based on mass spectrometry (MS) have emerged as powerful tools to contextualise existing genomic information and to create quantitative protein profiles from plasma, tissues or cell lines of various species. Proteomic approaches have been used increasingly in veterinary science to investigate biological processes responsible for growth, reproduction and pathological events. However, the adoption of proteomic approaches by veterinary investigators lags behind that of researchers in the human medical field. Furthermore, in contrast to human proteomics studies, interpretation of veterinary proteomic data is difficult due to the limited protein databases available for many animal species. This review article examines the current use of advanced proteomics techniques for evaluation of animal health and welfare and covers the current status of clinical veterinary proteomics research, including successful protein identification and data interpretation studies. It includes a description of an emerging tool, sequential window acquisition of all theoretical fragment ion mass spectra (SWATH-MS), available on selected mass spectrometry instruments. This newly developed data acquisition technique combines advantages of discovery and targeted proteomics approaches, and thus has the potential to advance the veterinary proteomics field by enhancing identification and reproducibility of proteomics data.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Other 8 16%
Student > Ph. D. Student 7 14%
Researcher 6 12%
Student > Doctoral Student 5 10%
Student > Master 4 8%
Other 6 12%
Unknown 15 29%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 14 27%
Agricultural and Biological Sciences 9 18%
Biochemistry, Genetics and Molecular Biology 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Medicine and Dentistry 2 4%
Other 3 6%
Unknown 18 35%
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 07 December 2017.
All research outputs
#17,292,294
of 25,382,440 outputs
Outputs from Veterinary Journal
#1,310
of 2,436 outputs
Outputs of similar age
#216,092
of 338,252 outputs
Outputs of similar age from Veterinary Journal
#13
of 41 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,436 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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 338,252 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 41 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 58% of its contemporaries.