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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 Comparing Peptide Spectra Matches Across Search Engines
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    Chapter 6 Calculation of False Discovery Rate for Peptide and Protein Identification
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    Chapter 7 Methods and Algorithms for Quantitative Proteomics by Mass Spectrometry
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    Chapter 8 Interpretation of Tandem Mass Spectra of Posttranslationally Modified Peptides
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    Chapter 9 Solution to Dark Matter Identified by Mass-Tolerant Database Search
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    Chapter 10 Phosphoproteomics Profiling to Identify Altered Signaling Pathways and Kinase-Targeted Cancer Therapies
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    Chapter 11 Mass Spectrometry-Based Characterization of Ub- and UbL-Modified Proteins
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    Chapter 12 Targeted Proteomics as a Tool for Quantifying Urine-Based Biomarkers
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    Chapter 13 Data Imputation in Merged Isobaric Labeling-Based Relative Quantification Datasets
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    Chapter 14 Clustering Clinical Data in R
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    Chapter 15 Review of Issues and Solutions to Data Analysis Reproducibility and Data Quality in Clinical Proteomics
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    Chapter 16 Review of Batch Effects Prevention, Diagnostics, and Correction Approaches
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    Chapter 17 Using the Object-Oriented PowerShell for Simple Proteomics Data Analysis
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    Chapter 18 Considerations in the Analysis of Hydrogen Exchange Mass Spectrometry Data
Attention for Chapter 14: Clustering Clinical Data in R
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Chapter title
Clustering Clinical Data in R
Chapter number 14
Book title
Mass Spectrometry Data Analysis in Proteomics
Published by
Humana, New York, NY, September 2019
DOI 10.1007/978-1-4939-9744-2_14
Pubmed ID
Book ISBNs
978-1-4939-9743-5, 978-1-4939-9744-2
Authors

Ana Pina, Maria Paula Macedo, Roberto Henriques, Pina, Ana, Macedo, Maria Paula, Henriques, Roberto

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 20%
Other 2 10%
Researcher 2 10%
Student > Doctoral Student 1 5%
Professor 1 5%
Other 3 15%
Unknown 7 35%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 15%
Computer Science 3 15%
Medicine and Dentistry 2 10%
Nursing and Health Professions 1 5%
Unknown 11 55%