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Phospho-Proteomics

Overview of attention for book
Cover of 'Phospho-Proteomics'

Table of Contents

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    Book Overview
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    Chapter 1 A High-Resolution Two Dimensional Gel- and Pro-Q DPS-Based Proteomics Workflow for Phosphoprotein Identification and Quantitative Profiling
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    Chapter 2 Phospho-Proteomics
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    Chapter 3 Identification of Oxidative Stress-Induced Tyrosine Phosphorylated Proteins by Immunoprecipitation and Mass Spectrometry
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    Chapter 4 Enrichment and Characterization of Phosphopeptides by Immobilized Metal Affinity Chromatography (IMAC) and Mass Spectrometry
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    Chapter 5 The Use of Titanium Dioxide Micro-Columns to Selectively Isolate Phosphopeptides from Proteolytic Digests
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    Chapter 6 Enrichment and Separation of Mono- and Multiply Phosphorylated Peptides Using Sequential Elution from IMAC Prior to Mass Spectrometric Analysis
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    Chapter 7 Use of Stable Isotope Labeling by Amino Acids in Cell Culture (SILAC) for Phosphotyrosine Protein Identification and Quantitation
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    Chapter 8 Hydrophilic Interaction Chromatography for Fractionation and Enrichment of the Phosphoproteome
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    Chapter 9 SILAC for Global Phosphoproteomic Analysis
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    Chapter 10 Quantitative Phospho-proteomics Based on Soluble Nanopolymers
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    Chapter 11 Profiling the Tyrosine Phosphorylation State Using SH2 Domains
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    Chapter 12 An Overview of the Qualitative Analysis of Phosphoproteins by Mass Spectrometry
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    Chapter 13 The Analysis of Phosphoproteomes by Selective Labelling and Advanced Mass Spectrometric Techniques
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    Chapter 14 On-Line Liquid Chromatography Electron Capture Dissociation for the Characterization of Phosphorylation Sites in Proteins
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    Chapter 15 Quantification of Protein Phosphorylation by μLC-ICP-MS
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    Chapter 16 Reverse-Phase Diagonal Chromatography for Phosphoproteome Research
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    Chapter 17 Chemical Tagging Strategies for Mass Spectrometry-Based Phospho-proteomics
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    Chapter 18 Antibody array platform to monitor protein tyrosine phosphorylation in mammalian cells.
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    Chapter 19 Protein Tyrosine Kinase Characterization Based on Fully Automated Synthesis of (Phospho) Peptide Arrays in Microplates
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    Chapter 20 Kinome Profiling Using Peptide Arrays in Eukaryotic Cells
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    Chapter 21 ProMoST: A Tool for Calculating the p I and Molecular Mass of Phosphorylated and Modified Proteins on Two-Dimensional Gels
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    Chapter 22 Kinase-Specific Prediction of Protein Phosphorylation Sites
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    Chapter 23 Reconstructing Regulatory Kinase Pathways from Phosphopeptide Data: A Bioinformatics Approach
Attention for Chapter 1: A High-Resolution Two Dimensional Gel- and Pro-Q DPS-Based Proteomics Workflow for Phosphoprotein Identification and Quantitative Profiling
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (59th percentile)

Mentioned by

patent
1 patent

Readers on

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28 Mendeley
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1 CiteULike
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Chapter title
A High-Resolution Two Dimensional Gel- and Pro-Q DPS-Based Proteomics Workflow for Phosphoprotein Identification and Quantitative Profiling
Chapter number 1
Book title
Phospho-Proteomics
Published in
Methods in molecular biology, January 2009
DOI 10.1007/978-1-60327-834-8_1
Pubmed ID
Book ISBNs
978-1-60327-833-1, 978-1-60327-834-8
Authors

Ganesh K. Agrawal, Jay J. Thelen

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 4%
China 1 4%
Unknown 26 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 18%
Student > Doctoral Student 4 14%
Professor 4 14%
Researcher 4 14%
Student > Master 3 11%
Other 6 21%
Unknown 2 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 50%
Medicine and Dentistry 5 18%
Biochemistry, Genetics and Molecular Biology 2 7%
Immunology and Microbiology 2 7%
Computer Science 1 4%
Other 1 4%
Unknown 3 11%

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 14 December 2017.
All research outputs
#4,564,610
of 14,798,224 outputs
Outputs from Methods in molecular biology
#1,349
of 8,798 outputs
Outputs of similar age
#106,297
of 276,378 outputs
Outputs of similar age from Methods in molecular biology
#6
of 7 outputs
Altmetric has tracked 14,798,224 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,798 research outputs from this source. They receive a mean Attention Score of 2.5. This one has done well, scoring higher than 79% 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 276,378 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 59% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one.