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Cancer Gene Profiling

Overview of attention for book
Attention for Chapter 11: Application of Proteomics in Cancer Biomarker Discovery: GeLC-MS/MS
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1 tweeter

Citations

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2 Dimensions

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4 Mendeley
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Chapter title
Application of Proteomics in Cancer Biomarker Discovery: GeLC-MS/MS
Chapter number 11
Book title
Cancer Gene Profiling
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3204-7_11
Pubmed ID
Book ISBNs
978-1-4939-3203-0, 978-1-4939-3204-7
Authors

Pedro R. Cutillas, Tatjana Crnogorac-Jurcevic

Editors

Robert Grützmann, Christian Pilarsky

Abstract

Proteomic approaches are being increasingly applied to study multiple facets of healthy and diseased processes. In particular, the application of global proteome profiling in the field of oncology is already starting to shape the diagnostic, prognostic, monitoring, and therapeutic approaches. At the heart of such approaches lies a quest for clinically relevant biomarkers, particularly arising from global analyses of body fluids, as, in major part, they represent easily accessible and noninvasive matrices. A detailed protocol of one of the popular approaches for global proteome profiling, SDS-PAGE-liquid chromatography-tandem mass spectrometry or GeLC-MS/MS, and its application for biomarker discovery in urine is provided here.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 25%
Student > Bachelor 1 25%
Unknown 2 50%
Readers by discipline Count As %
Agricultural and Biological Sciences 1 25%
Medicine and Dentistry 1 25%
Unknown 2 50%

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 October 2016.
All research outputs
#15,345,334
of 17,361,274 outputs
Outputs from Methods in molecular biology
#6,843
of 9,915 outputs
Outputs of similar age
#288,347
of 350,660 outputs
Outputs of similar age from Methods in molecular biology
#782
of 1,159 outputs
Altmetric has tracked 17,361,274 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 9,915 research outputs from this source. They receive a mean Attention Score of 2.7. 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 350,660 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 1,159 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.