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Shotgun Proteomics

Overview of attention for book
Cover of 'Shotgun Proteomics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Survey of shotgun proteomics.
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    Chapter 2 LC-MALDI-TOF/TOF for Shotgun Proteomics.
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    Chapter 3 Fully automatable multidimensional reversed-phase liquid chromatography with online tandem mass spectrometry.
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    Chapter 4 GeLC-MS/MS Analysis of Complex Protein Mixtures.
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    Chapter 5 IPG Strip-Based Peptide Fractionation for Shotgun Proteomics.
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    Chapter 6 SILAC Yeast: From Labeling to Comprehensive Proteome Quantification.
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    Chapter 7 Analysis of proteome dynamics in mice by isotopic labeling.
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    Chapter 8 Stable Isotope Labeling in Mammals (SILAM).
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    Chapter 9 Analysis of individual protein turnover in live animals on a proteome-wide scale.
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    Chapter 10 Determining Protein Subcellular Localization in Mammalian Cell Culture with Biochemical Fractionation and iTRAQ 8-Plex Quantification.
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    Chapter 11 Brain Quantitative Proteomics Combining GeLC-MS and Isotope-Coded Protein Labeling (ICPL)
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    Chapter 12 Employing TMT Quantification in a Shotgun-MS Platform.
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    Chapter 13 Employing TMT Quantification in Shotgun-MS Proteomic Analysis: A Focus on Skeletal Muscle.
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    Chapter 14 Spectral counting label-free proteomics.
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    Chapter 15 Quantification of Proteins by Label-Free LC-MS(E.).
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    Chapter 16 Bioinformatics for proteomics: opportunities at the interface between the scientists, their experiments, and the community.
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    Chapter 17 Identification of DNA Damage Checkpoint-Dependent Protein Interactions in Saccharomyces cerevisiae Using Quantitative Mass Spectrometry.
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    Chapter 18 Application of shotgun proteomics for discovery-driven protein-protein interaction.
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    Chapter 19 Mapping protein complexes using covalently linked antibodies and isobaric mass tags.
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    Chapter 20 Biomarker verification using selected reaction monitoring and shotgun proteomics.
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    Chapter 21 Use of Universal Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC)-Based Selected Reaction Monitoring (SRM) Approach for Verification of Breast Cancer-Related Protein Markers.
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    Chapter 22 The Secretome Analysis by High-Throughput Proteomics and Multiple Reaction Monitoring (MRM).
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    Chapter 23 Preparation of heteroelement-incorporated and stable isotope-labeled protein standards for quantitative proteomics.
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    Chapter 24 One-source peptide/phosphopeptide ratio standards for accurate and site-specific determination of the degree of phosphorylation.
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    Chapter 25 Quantitative glycoproteomics for N-glycoproteome profiling.
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    Chapter 26 A practical recipe to survey phosphoproteomes.
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    Chapter 27 Quantitation of the Phosphoproteome Using the Library-Assisted eXtracted Ion Chromatogram (LAXIC) Strategy.
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    Chapter 28 Fast, efficient, and quality-controlled phosphopeptide enrichment from minute sample amounts using titanium dioxide.
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    Chapter 29 Quantifying small molecule-induced changes in cellular protein expression and posttranslational modifications using isobaric mass tags.
  31. Altmetric Badge
    Chapter 30 Analysis of protein structure by cross-linking combined with mass spectrometry.
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    Chapter 31 Top-down proteomics by means of orbitrap mass spectrometry.
Attention for Chapter 11: Brain Quantitative Proteomics Combining GeLC-MS and Isotope-Coded Protein Labeling (ICPL)
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Chapter title
Brain Quantitative Proteomics Combining GeLC-MS and Isotope-Coded Protein Labeling (ICPL)
Chapter number 11
Book title
Shotgun Proteomics
Published in
Methods in molecular biology, April 2014
DOI 10.1007/978-1-4939-0685-7_11
Pubmed ID
24791988
Book ISBNs
978-1-4939-0684-0, 978-1-4939-0685-7
Authors

Giuseppina Maccarrone, Maria Lebar, Daniel Martins-de-Souza

Editors

Daniel Martins-de-Souza

Abstract

Proteomics has been revolutionized by the rapid advance of mass spectrometric instrumentations and techniques. Parallel methodologies for the quantification of proteomes also evolved, including in vitro stable isotope labeling. Here, we present a protocol for employing isotope-coded protein labeling (ICPL) as part of a shotgun proteomics workflow denoting its advantages and disadvantages. This protocol is suitable to studying any proteome of interest, only requiring a specific sample preparation and protein identification. Given our expertise, descriptions here are centered on the study of brain disorders.

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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 readers

Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Other 2 14%
Researcher 2 14%
Professor > Associate Professor 2 14%
Student > Ph. D. Student 2 14%
Unspecified 1 7%
Other 2 14%
Unknown 3 21%
Readers by discipline Count As %
Chemistry 5 36%
Unspecified 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Computer Science 1 7%
Business, Management and Accounting 1 7%
Other 2 14%
Unknown 3 21%
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 06 May 2014.
All research outputs
#18,371,959
of 22,755,127 outputs
Outputs from Methods in molecular biology
#7,865
of 13,089 outputs
Outputs of similar age
#163,589
of 226,068 outputs
Outputs of similar age from Methods in molecular biology
#56
of 153 outputs
Altmetric has tracked 22,755,127 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,089 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 153 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.

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