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Immunoproteomics

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Cover of 'Immunoproteomics'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to the Immune System
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    Chapter 2 Immunoproteomics Methods and Techniques
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    Chapter 3 Classical Immunoproteomics: Serological Proteome Analysis (SERPA) for Antigen Identification
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    Chapter 4 Profiling of Cytokine and Chemokine Responses Using Multiplex Bead Array Technology
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    Chapter 5 Preparation of the Low Molecular Weight Serum Proteome for Mass Spectrometry Analysis
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    Chapter 6 Enriching for Low-Abundance Serum Proteins Using ProteoMiner™ and Protein-Level HPLC
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    Chapter 7 Identification of the Antigen Content of Electroimmunoprecipitates
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    Chapter 8 Detection of Human Norovirus-Specific Antibodies Using the Luciferase Immunoprecipitation System (LIPS) Assay
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    Chapter 9 Intact Mass Spectrometry Analysis of Immuno-Isolated Human Therapeutic Antibodies from Serum
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    Chapter 10 Antigen Identification for Cell-Binding Antibodies Using Ligand-Directed Crosslinking and Biotin Transfer
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    Chapter 11 Whole-Genome Phage Display Libraries: A Powerful Tool for Antigen Discovery
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    Chapter 12 Multiplexed Detection of Autoantibodies to Glycopeptides Using Microarray
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    Chapter 13 Construction and Screening of an Antigen-Derived Peptide Library Displayed on Yeast Cell Surface for CD4+ T Cell Epitope Identification
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    Chapter 14 Isolation of Major Histocompatibility Complex (MHC)-Associated Peptides by Immunoaffinity Purification
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    Chapter 15 Enhanced Mass Spectrometry Detection of MHC Peptides
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    Chapter 16 Enrichment of Phosphorylated MHC Peptides with Immobilized Metal Affinity Chromatography and Titanium Dioxide Particles
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    Chapter 17 Mass Spectrometric Identification and Molecular Modeling of Glycopeptides Presented by MHC Class I and II Processing Pathways
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    Chapter 18 Genome-Based Bioinformatic Prediction of Major Histocompatibility (MHC)
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    Chapter 19 Enhancing Mass Spectrometry-Based MHC-I Peptide Identification Through a Targeted Database Search Approach
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    Chapter 20 Prioritization of Therapeutic Targets of Inflammation Using Proteomics, Bioinformatics, and In Silico Cell-Cell Interactomics
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    Chapter 21 Genomics-Driven Immunoproteomics: An Integrative Platform to Uncover Important Biomarkers for Human Diseases
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    Chapter 22 Identification of Antigens in Immune Complexes
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    Chapter 23 Analysis and Characterization of Immune Cells and Their Activation Status by Whole-Cell MALDI-TOF Mass Spectrometry
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    Chapter 24 A Molecular Immunoproteomics Approach to Assess the Viral Antigenicity of Influenza
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    Chapter 25 Immunoproteomic Biomarkers: From Publication to Personalized Medicine
Attention for Chapter 1: Introduction to the Immune System
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Chapter title
Introduction to the Immune System
Chapter number 1
Book title
Immunoproteomics
Published by
Humana, New York, NY, July 2019
DOI 10.1007/978-1-4939-9597-4_1
Pubmed ID
Book ISBNs
978-1-4939-9596-7, 978-1-4939-9597-4
Authors

Scott McComb, Aude Thiriot, Bassel Akache, Lakshmi Krishnan, Felicity Stark, McComb, Scott, Thiriot, Aude, Akache, Bassel, Krishnan, Lakshmi, Stark, Felicity

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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 447 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Netherlands 1 <1%
Taiwan 1 <1%
Unknown 444 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 70 16%
Student > Master 51 11%
Student > Ph. D. Student 39 9%
Student > Doctoral Student 21 5%
Researcher 17 4%
Other 42 9%
Unknown 207 46%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 55 12%
Medicine and Dentistry 50 11%
Agricultural and Biological Sciences 26 6%
Immunology and Microbiology 25 6%
Pharmacology, Toxicology and Pharmaceutical Science 23 5%
Other 53 12%
Unknown 215 48%