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

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

Table of Contents

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    Book Overview
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    Chapter 1 Transformation, Normalization, and Batch Effect in the Analysis of Mass Spectrometry Data for Omics Studies
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    Chapter 2 Automated Alignment of Mass Spectrometry Data Using Functional Geometry
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    Chapter 3 The Analysis of Peptide-Centric Mass-Spectrometry Data Utilizing Information About the Expected Isotope Distribution
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    Chapter 4 Probabilistic and Likelihood-Based Methods for Protein Identification from MS/MS Data
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    Chapter 5 An MCMC-MRF Algorithm for Incorporating Spatial Information in IMS Proteomic Data Processing
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    Chapter 6 Mass Spectrometry Analysis Using MALDIquant
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    Chapter 7 Model-Based Analysis of Quantitative Proteomics Data with Data Independent Acquisition Mass Spectrometry
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    Chapter 8 The Analysis of Human Serum Albumin Proteoforms Using Compositional Framework
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    Chapter 9 Variability Assessment of Label-Free LC-MS Experiments for Difference Detection
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    Chapter 10 Statistical Approach for Biomarker Discovery Using Label-Free LC-MS Data: An Overview
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    Chapter 11 Bayesian Posterior Integration for Classification of Mass Spectrometry Data
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    Chapter 12 Logistic Regression Modeling on Mass Spectrometry Data in Proteomics Case-Control Discriminant Studies
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    Chapter 13 Robust and Confident Predictor Selection in Metabolomics
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    Chapter 14 On the Combination of Omics Data for Prediction of Binary Outcomes
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    Chapter 15 Statistical Analysis of Lipidomics Data in a Case-Control Study
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