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Modern Proteomics – Sample Preparation, Analysis and Practical Applications

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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 21: Discovery of Candidate Biomarkers
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Citations

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Chapter title
Discovery of Candidate Biomarkers
Chapter number 21
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_21
Pubmed ID
Book ISBNs
978-3-31-941446-1, 978-3-31-941448-5
Authors

John E. Wiktorowicz, Kizhake V. Soman

Editors

Hamid Mirzaei, Martin Carrasco

Abstract

Properly performed, biomarker discovery can lead to effective candidates that can ultimately serve as predictors of disease, medical condition, define therapeutic parameters, and many other applications in medicine. Preferably, biomarkers comprise a panel of indicators, e.g. proteins and/or peptides that can be predictive or diagnostic of the medical condition of interest. Emphasis here is placed on "panel," as single candidates are rarely sufficient to provide the necessary sensitivity and specificity. To develop an effective panel that survives the development process described in Chap. 19 , proper experimental design and attention to important statistical parameters are critical to ensure success. Errors in discovery can lead to an inefficient use of expensive resources, as these may not be uncovered until the latter stages in biomarker development. Hence, accuracy, precision, and an estimate of the power of the proposed analyses are critical in the discovery of the panel of candidate biomarkers by proteomic methods, as is the selection of statistical approaches to refine and appropriately reduce the dataset for subsequent confirmatory assays.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 5%
Unknown 18 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 26%
Other 3 16%
Lecturer > Senior Lecturer 2 11%
Student > Bachelor 1 5%
Student > Master 1 5%
Other 3 16%
Unknown 4 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 21%
Medicine and Dentistry 4 21%
Agricultural and Biological Sciences 4 21%
Veterinary Science and Veterinary Medicine 1 5%
Computer Science 1 5%
Other 1 5%
Unknown 4 21%