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Mass Spectrometry Data Analysis in Proteomics

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Cover of 'Mass Spectrometry Data Analysis in Proteomics'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Mass Spectrometry-Based Proteomics
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    Chapter 2 LC-MS Spectra Processing
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    Chapter 3 Isotopic Distributions
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    Chapter 4 Retention Time Prediction and Protein Identification
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    Chapter 5 Algorithms for Database-Dependent Search of MS/MS Data
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    Chapter 6 Interpretation of Tandem Mass Spectra of Posttranslationally Modified Peptides
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    Chapter 7 Improving Peptide Identification Using Empirical Scoring Systems
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    Chapter 8 Methods and Algorithms for Quantitative Proteomics by Mass Spectrometry
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    Chapter 9 Computational Approaches to Selected Reaction Monitoring Assay Design
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    Chapter 10 Feature selection and machine learning with mass spectrometry data.
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    Chapter 11 Considerations in the Analysis of Hydrogen Exchange Mass Spectrometry Data
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    Chapter 12 Permethylated N-glycan analysis with mass spectrometry.
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    Chapter 13 Mass Spectrometry Methods for Studying Glycosylation in Cancer
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    Chapter 14 Proteomics data exchange and storage: the need for common standards and public repositories.
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    Chapter 15 Tools for Protein Posttranslational Modifications Analysis: FAK, a Case Study
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    Chapter 16 Proteomic Strategies to Characterize Signaling Pathways
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    Chapter 17 Simple Proteomics Data Analysis in the Object-Oriented PowerShell
Attention for Chapter 4: Retention Time Prediction and Protein Identification
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Citations

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Chapter title
Retention Time Prediction and Protein Identification
Chapter number 4
Book title
Mass Spectrometry Data Analysis in Proteomics
Published in
Methods in molecular biology, January 2013
DOI 10.1007/978-1-62703-392-3_4
Pubmed ID
Book ISBNs
978-1-62703-391-6, 978-1-62703-392-3
Authors

Alex A. Henneman, Magnus Palmblad

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 27%
Professor > Associate Professor 3 20%
Student > Postgraduate 2 13%
Student > Master 2 13%
Student > Bachelor 1 7%
Other 0 0%
Unknown 3 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 27%
Agricultural and Biological Sciences 3 20%
Chemical Engineering 1 7%
Computer Science 1 7%
Medicine and Dentistry 1 7%
Other 1 7%
Unknown 4 27%