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Proteogenomics for understanding oncology: recent advances and future prospects

Overview of attention for article published in Expert Review of Proteomics, January 2016
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Article details
Title
Proteogenomics for understanding oncology: recent advances and future prospects
Published in
Expert Review of Proteomics, January 2016
DOI 10.1586/14789450.2016.1136217
Pubmed ID
Authors
Abstract

The concept of proteogenomics has emerged rapidly as a valuable approach to integrate mass spectrometry-derived proteomic data with genomic and transcriptomic data. It is used to harness the full potential of the former dataset in the discovery of potential biomarkers, therapeutic targets and novel proteins associated with various biological processes including diseases. Proteogenomic strategies have been successfully utilized to identify novel genes and redefine annotation of existing gene models in various genomes. In recent years, this approach has been extended to the field of cancer biology to unravel complexities in the tumor genomes and proteomes. Standard proteomics workflows employing translated cancer genomes and transcriptomes can potentially identify peptides from mutant proteins, splice variants and fusion proteins in the tumor proteome, which in addition to the currently available biomarker panels can serve as potential diagnostic and prognostic biomarkers, besides having therapeutic utility. This review focuses on the role of proteogenomics to understand cancer biology.

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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Netherlands 1 2%
Unknown 44 98%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 10 22%
Professor > Associate Professor 6 13%
Researcher 4 9%
Student > Doctoral Student 3 7%
Other 2 4%
Other 7 16%
Unknown 13 29%
Readers by discipline
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 36%
Medicine and Dentistry 6 13%
Agricultural and Biological Sciences 2 4%
Veterinary Science and Veterinary Medicine 1 2%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Other 3 7%
Unknown 16 36%
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 26 December 2015.
All research outputs
#20,299,108
of 22,836,570 outputs
Outputs from Expert Review of Proteomics
#599
of 685 outputs
Outputs of similar age
#333,352
of 396,507 outputs
Outputs of similar age from Expert Review of Proteomics
#17
of 18 outputs
Altmetric has tracked 22,836,570 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 685 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 1st percentile – i.e., 1% 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 396,507 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.