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Proteomics of protein post-translational modifications implicated in neurodegeneration

Overview of attention for article published in Translational Neurodegeneration, October 2014
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Title
Proteomics of protein post-translational modifications implicated in neurodegeneration
Published in
Translational Neurodegeneration, October 2014
DOI 10.1186/2047-9158-3-23
Pubmed ID
Authors

Ru-Jing Ren, Eric B Dammer, Gang Wang, Nicholas T Seyfried, Allan I Levey

Abstract

Mass spectrometry (MS)-based proteomics has developed into a battery of approaches that is exceedingly adept at identifying with high mass accuracy and precision any of the following: oxidative damage to proteins (redox proteomics), phosphorylation (phosphoproteomics), ubiquitination (diglycine remnant proteomics), protein fragmentation (degradomics), and other posttranslational modifications (PTMs). Many studies have linked these PTMs to pathogenic mechanisms of neurodegeneration. To date, identifying PTMs on specific pathology-associated proteins has proven to be a valuable step in the evaluation of functional alteration of proteins and also elucidates biochemical and structural explanations for possible pathophysiological mechanisms of neurodegenerative diseases. This review provides an overview of methods applicable to the identification and quantification of PTMs on proteins and enumerates historic, recent, and potential future research endeavours in the field of proteomics furthering the understanding of PTM roles in the pathogenesis of neurodegeneration.

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Mendeley readers

The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Denmark 1 <1%
Germany 1 <1%
Unknown 116 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 21%
Researcher 19 16%
Student > Master 17 14%
Student > Bachelor 12 10%
Student > Doctoral Student 9 7%
Other 23 19%
Unknown 16 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 29 24%
Biochemistry, Genetics and Molecular Biology 24 20%
Neuroscience 10 8%
Medicine and Dentistry 10 8%
Chemistry 9 7%
Other 18 15%
Unknown 21 17%