Computational and Statistical Methods for Protein Quantification by Mass Spectrometry

Autor: Ingvar Eidhammer

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Legare: Copertă tare

Editura: John Wiley and Sons Ltd

Disponibilitate: În depozitul extern

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610.59 lei

The definitive introduction to data analysis in quantitative proteomics This book provides all the n...

Informații despre carte

Autor

Ingvar Eidhammer

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2013

Pagini

354

EAN

9781119964001

ISBN

1119964008

Enbook ID

01250395

Editura

John Wiley and Sons Ltd

Greutate

672

Dimensiuni

168 x 228 x 26

Descriere completă

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.

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