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Protein Terminal Profiling

Overview of attention for book
Cover of 'Protein Terminal Profiling'

Table of Contents

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    Book Overview
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    Chapter 1 [14C]-Acetyl-Coenzyme A-Based In Vitro N-Terminal Acetylation Assay
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    Chapter 2 DTNB-Based Quantification of In Vitro Enzymatic N-Terminal Acetyltransferase Activity
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    Chapter 3 SILProNAQ: A Convenient Approach for Proteome-Wide Analysis of Protein N-Termini and N-Terminal Acetylation Quantitation
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    Chapter 4 Profiling of Protein N-Termini and Their Modifications in Complex Samples
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    Chapter 5 Protease Substrate Profiling by N-Terminal COFRADIC
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    Chapter 6 Doublet N-Terminal Oriented Proteomics for N-Terminomics and Proteolytic Processing Identification
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    Chapter 7 Multidimensional Analysis of Protease Substrates and Their Cellular Origins in Mixed Secretomes from Multiple Cell Types
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    Chapter 8 System-Wide Profiling of Protein Amino Termini from Formalin-Fixed, Paraffin-Embedded Tissue Specimens for the Identification of Novel Substrates
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    Chapter 9 Identification of Carboxypeptidase Substrates by C-Terminal COFRADIC
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    Chapter 10 ProC-TEL: Profiling of Protein C-Termini by Enzymatic Labeling
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    Chapter 11 Determining Protease Substrates Within a Complex Protein Background Using the PROtein TOpography and Migration Analysis Platform (PROTOMAP)
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    Chapter 12 Multiplexed Protease Specificity Profiling Using Isobaric Labeling
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    Chapter 13 FPPS: Fast Profiling of Protease Specificity
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    Chapter 14 Profiling of Protease Cleavage Sites by Proteome-Derived Peptide Libraries and Quantitative Proteomics
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    Chapter 15 Prediction of Proteases Involved in Peptide Generation
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    Chapter 16 Live-Cell Imaging of Protease Activity: Assays to Screen Therapeutic Approaches
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    Chapter 17 Protein Translocation Assays to Probe Protease Function and Screen for Inhibitors
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    Chapter 18 Simultaneous Detection of Metalloprotease Activities in Complex Biological Samples Using the PrAMA (Proteolytic Activity Matrix Assay) Method
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    Chapter 19 Synthesis and Application of Activity-Based Probes for Proteases
Attention for Chapter 9: Identification of Carboxypeptidase Substrates by C-Terminal COFRADIC
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

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Chapter title
Identification of Carboxypeptidase Substrates by C-Terminal COFRADIC
Chapter number 9
Book title
Protein Terminal Profiling
Published in
Methods in molecular biology, March 2017
DOI 10.1007/978-1-4939-6850-3_9
Pubmed ID
28315247
Book ISBNs
978-1-4939-6849-7, 978-1-4939-6850-3
Authors

Tanco, Sebastian, Aviles, Francesc Xavier, Gevaert, Kris, Lorenzo, Julia, Van Damme, Petra, Sebastian Tanco, Francesc Xavier Aviles, Kris Gevaert, Julia Lorenzo, Petra Van Damme

Editors

Oliver Schilling

Abstract

We here present a detailed procedure for studying protein C-termini and their posttranslational modifications by C-terminal COFRADIC. In fact, this procedure can enrich for both C-terminal and N-terminal peptides through a combination of a strong cation exchange fractionation step at low pH, which removes the majority of nonterminal peptides in whole-proteome digests, while the actual COFRADIC step segregates C-terminal peptides from N-terminal peptides. When used in a differential mode, C-terminal COFRADIC allows for the identification of neo-C-termini generated by the action of proteases, which in turn leads to the identification of protease substrates. More specifically, this technology can be applied to determine the natural substrate repertoire of carboxypeptidases on a proteome-wide scale.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 18%
Student > Master 2 18%
Researcher 2 18%
Student > Ph. D. Student 1 9%
Unspecified 1 9%
Other 2 18%
Unknown 1 9%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 55%
Chemical Engineering 1 9%
Unspecified 1 9%
Computer Science 1 9%
Unknown 2 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 21 March 2017.
All research outputs
#12,971,722
of 22,959,818 outputs
Outputs from Methods in molecular biology
#3,291
of 13,136 outputs
Outputs of similar age
#161,203
of 334,650 outputs
Outputs of similar age from Methods in molecular biology
#57
of 309 outputs
Altmetric has tracked 22,959,818 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,136 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 74% 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 334,650 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 309 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.

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