Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry


ISBN: 978-3-319-45807-6 (Print) 978-3-319-45809-0 (Online)

Table of contents (15 chapters)

  1. Front Matter

    Pages i-viii

  2. Chapter

    Pages 1-21

    Transformation, Normalization, and Batch Effect in the Analysis of Mass Spectrometry Data for Omics Studies

  3. Chapter

    Pages 23-43

    Automated Alignment of Mass Spectrometry Data Using Functional Geometry

  4. Chapter

    Pages 45-64

    The Analysis of Peptide-Centric Mass-Spectrometry Data Utilizing Information About the Expected Isotope Distribution

  5. Chapter

    Pages 65-79

    Probabilistic and Likelihood-Based Methods for Protein Identification from MS/MS Data

  6. Chapter

    Pages 81-99

    An MCMC-MRF Algorithm for Incorporating Spatial Information in IMS Proteomic Data Processing

  7. Chapter

    Pages 101-124

    Mass Spectrometry Analysis Using MALDIquant

  8. Chapter

    Pages 125-140

    Model-Based Analysis of Quantitative Proteomics Data with Data Independent Acquisition Mass Spectrometry

  9. Chapter

    Pages 141-155

    The Analysis of Human Serum Albumin Proteoforms Using Compositional Framework

  10. Chapter

    Pages 157-176

    Variability Assessment of Label-Free LC-MS Experiments for Difference Detection

  11. Chapter

    Pages 177-201

    Statistical Approach for Biomarker Discovery Using Label-Free LC-MS Data: An Overview

  12. Chapter

    Pages 203-211

    Bayesian Posterior Integration for Classification of Mass Spectrometry Data

  13. Chapter

    Pages 213-238

    Logistic Regression Modeling on Mass Spectrometry Data in Proteomics Case-Control Discriminant Studies

  14. Chapter

    Pages 239-257

    Robust and Confident Predictor Selection in Metabolomics

  15. Chapter

    Pages 259-275

    On the Combination of Omics Data for Prediction of Binary Outcomes

  16. Chapter

    Pages 277-295

    Statistical Analysis of Lipidomics Data in a Case-Control Study