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Modern Proteomics – Sample Preparation, Analysis and Practical Applications

Overview of attention for book
Cover of 'Modern Proteomics – Sample Preparation, Analysis and Practical Applications'

Table of Contents

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    Book Overview
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    Chapter 1 Proteomes, Their Compositions and Their Sources
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    Chapter 2 Protein Fractionation and Enrichment Prior to Proteomics Sample Preparation
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    Chapter 3 Sample Preparation for Mass Spectrometry-Based Proteomics; from Proteomes to Peptides
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    Chapter 4 Plant Structure and Specificity – Challenges and Sample Preparation Considerations for Proteomics
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    Chapter 5 Improving Proteome Coverage by Reducing Sample Complexity via Chromatography
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    Chapter 6 Database Search Engines: Paradigms, Challenges and Solutions
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    Chapter 7 Mass Analyzers and Mass Spectrometers
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    Chapter 8 Top-Down Mass Spectrometry: Proteomics to Proteoforms
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    Chapter 9 Platforms and Pipelines for Proteomics Data Analysis and Management
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    Chapter 10 Tandem Mass Spectrum Sequencing: An Alternative to Database Search Engines in Shotgun Proteomics
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    Chapter 11 Visualization, Inspection and Interpretation of Shotgun Proteomics Identification Results
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    Chapter 12 Protein Inference
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    Chapter 13 Modification Site Localization in Peptides
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    Chapter 14 Useful Web Resources
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    Chapter 15 Mass Spectrometry-Based Protein Quantification
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    Chapter 16 Bioinformatics Tools for Proteomics Data Interpretation
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    Chapter 17 Identification, Quantification, and Site Localization of Protein Posttranslational Modifications via Mass Spectrometry-Based Proteomics
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    Chapter 18 Protein-Protein Interaction Detection Via Mass Spectrometry-Based Proteomics
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    Chapter 19 Protein Structural Analysis via Mass Spectrometry-Based Proteomics
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    Chapter 20 Introduction to Clinical Proteomics
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    Chapter 21 Discovery of Candidate Biomarkers
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    Chapter 22 Statistical Approaches to Candidate Biomarker Panel Selection
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    Chapter 23 Qualification and Verification of Protein Biomarker Candidates
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    Chapter 24 Protocol for Standardizing High-to-Moderate Abundance Protein Biomarker Assessments Through an MRM-with-Standard-Peptides Quantitative Approach
Attention for Chapter 7: Mass Analyzers and Mass Spectrometers
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Chapter title
Mass Analyzers and Mass Spectrometers
Chapter number 7
Book title
Modern Proteomics – Sample Preparation, Analysis and Practical Applications
Published in
Advances in experimental medicine and biology, December 2016
DOI 10.1007/978-3-319-41448-5_7
Pubmed ID
27975216
Book ISBNs
978-3-31-941446-1, 978-3-31-941448-5
Authors

Anthony M. Haag

Editors

Hamid Mirzaei, Martin Carrasco

Abstract

Mass spectrometers are comprised of three main components: an ion source, a mass analyzer, and a detector. Ionization of the analyte occurs in the ion source and the resulting ions are counted at the detector. However, it is the mass analyzer that is responsible for determing the mass-to-charge ratio (m/z) of the ions (Jennings KR, Dolnikowski GG, Method Enzymol 193:37-61, 1990). Therefore, it is primarily the analyzer that allows the mass spectrometer to serve its primary goal - determining the mass of the analytes being measured. This becomes important in the field of molecular biology, where biomolecules may be of low molecular weight or often take on multiple charges (z) after ionization (Fenn JB, Mann M, Meng CK, Wong SF, Whitehouse CM, Science 246:64-71, 1989). For this reason, the choice of analyzer is dependant on the properties of the analyte after ionization and the requirements of the experiment being performed.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 277 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 277 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 54 19%
Student > Bachelor 48 17%
Student > Master 36 13%
Researcher 14 5%
Student > Doctoral Student 13 5%
Other 22 8%
Unknown 90 32%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 63 23%
Chemistry 49 18%
Pharmacology, Toxicology and Pharmaceutical Science 24 9%
Agricultural and Biological Sciences 13 5%
Unspecified 12 4%
Other 15 5%
Unknown 101 36%
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 17 September 2017.
All research outputs
#17,837,681
of 22,914,829 outputs
Outputs from Advances in experimental medicine and biology
#3,103
of 4,953 outputs
Outputs of similar age
#292,656
of 420,880 outputs
Outputs of similar age from Advances in experimental medicine and biology
#318
of 500 outputs
Altmetric has tracked 22,914,829 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,953 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 33rd percentile – i.e., 33% 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 420,880 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 500 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.

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