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Computational and Statistical Methods for Protein Quantification by Mass Spectrometry

By: Ingvar Eidhammer (Author), Harald Barsnes (Author), Geir Egil Eide (Author), Lennart Martens (Author)

John Wiley & Sons

Hardback | Dec 2012 | #201134 | ISBN-13: 9781119964001
Availability: Usually dispatched within 5 days Details
NHBS Price: £59.99 $73/€67 approx

About this book

This book provides all the necessary knowledge about mass spectrometry based proteomics methods and computational and statistical approaches to pursue the planning, design and analysis of quantitative proteomics experiments. The author’s carefully constructed approach allows readers to easily make the transition into the field of quantitative proteomics. Through detailed descriptions of wet-lab methods, computational approaches and statistical tools, this book covers the full scope of a quantitative experiment, allowing readers to acquire new knowledge as well as acting as a useful reference work for more advanced readers.

With clear and thorough descriptions of the various methods and approaches, this book is accessible to biologists, informaticians, and statisticians alike and is aimed at readers across the academic spectrum, from advanced undergraduate students to post doctorates entering the field.



1 Introduction
2 Correlations of mRNA and Protein Abundances
3 Protein-level Quantification
4 Mass Spectrometry and Protein Identification
5 Protein Quantification by Mass Spectrometry
6 Statistical Normalization 82
7 Experimental Normalization
8 Statistical Analysis
9 Label-based Quantification
10 Reporter-based MS/MS Quantification
11 Fragment-based MS/MS Quantification
12 Label-based Quantification by MS-spectra
13 Label-free Quantification by MS spectra
14 Label-free Quantification by MS/MS spectra
15 Targeted Quantification - Selected Reaction Monitoring
16 Absolute Quantification
17 Quantification of Posttranslational Modifications
18 Biomarkers
19 Standards and Databases
20 Appendix A: Statistics
21 Appendix B: Clustering and Discriminant Analysis


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