The definitive introduction to data analysis in quantitative proteomics
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.
Computational and Statistical Methods for Protein Quantification by Mass Spectrometry:
- Introduces the use of mass spectrometry in protein quantification and how the bioinformatics challenges in this field can be solved using statistical methods and various software programs.
- Is illustrated by a large number of figures and examples as well as numerous exercises.
- Provides both clear and rigorous descriptions of methods and approaches.
- Is thoroughly indexed and cross-referenced, combining the strengths of a text book with the utility of a reference work.
- Features detailed discussions of both wet-lab approaches and statistical and computational methods.
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.
Content:Chapter 1 Introduction (pages 1–11):
Chapter 2 Correlations of mRNA and Protein Abundances (pages 12–21):
Chapter 3 Protein Level Quantification (pages 22–26):
Chapter 4 Mass Spectrometry and Protein Identification (pages 27–47):
Chapter 5 Protein Quantification by Mass Spectrometry (pages 48–74):
Chapter 6 Statistical Normalization (pages 75–95):
Chapter 7 Experimental Normalization (pages 96–109):
Chapter 8 Statistical Analysis (pages 110–128):
Chapter 9 Label Based Quantification (pages 129–137):
Chapter 10 Reporter Based MS/MS Quantification (pages 138–154):
Chapter 11 Fragment Based MS/MS Quantification (pages 155–159):
Chapter 12 Label Based Quantification by MS Spectra (pages 160–184):
Chapter 13 Label free Quantification by MS Spectra (pages 185–204):
Chapter 14 Label Free Quantification by MS/MS Spectra (pages 205–217):
Chapter 15 Targeted Quantification – Selected Reaction Monitoring (pages 218–234):
Chapter 16 Absolute Quantification (pages 235–243):
Chapter 17 Quantification of Post?Translational Modifications (pages 244–253):
Chapter 18 Biomarkers (pages 254–258):
Chapter 19 Standards and Databases (pages 259–263):
Chapter 20 Appendix A: Statistics (pages 264–291):
Chapter 21 Appendix B: Clustering and Discriminant Analysis (pages 292–312):