Computational methods and data analysis for metabolomics / edited by Shuzhao Li. -- New York : Humana Press, 2020. – (58.17/M592/v.2104)

Contents

Preface

Contributors

1  Overview of Experimental Methods and Study Design in Metabolomics, and Statistical and Pathway Considerations

2  Metabolomics Data Processing Using XCMS

3  Metabolomics Data Preprocessing Using ADAP and MZmine 2

4  Metabolomics Data Processing Using OpenMS

5  Analysis of NMR Metabolomics Data

6  Key Concepts Surrounding Studies of Stable Isotope-Resolved Metabolomics

7  Extracting Biological Insight from Untargeted Lipidomics Data

8  Overview of Tandem Mass Spectral and Metabolite Databases for Metabolite Identification in Metabolomics

9  METLIN: A Tandem Mass Spectral Library of Standards

10  Metabolomic Data Exploration and Analysis with the Human Metabolome Database

11  De Novo Molecular Formula Annotation and Structure Elucidation Using SIRIUS 4

12  Annotation of Specialized Metabolites from High-Throughput and High-Resolution Mass Spectrometry Metabolomics

13  Feature-Based Molecular Networking for Metabolite Annotation

14  A Bioinformatics Primer to Data Science, with Examples for Metabolomics.

15  The Essential Toolbox of Data Science: Python, R, Git, and Docker

16  Predictive Modeling for Metabolomics Data

17  Using MetaboAnalyst 4.0 for Metabolomics Data Analysis, Interpretation, and Integration with Other Omics Data

18  Using Genome-Scale Metabolic Networks for Analysis, Visualization, and Integration of Targeted Metabolomics Data

19  Pathway Analysis for Targeted and Untargeted Metabolomics

20  Application of Metabolomics to Renal and Cardiometabolic Diseases

21  Using the IDEOM Workflow for LCMS-Based Metabolomics Studies of Drug Mechanisms

22  Analyzing Metabolomics Data for Environmental Health and Exposome Research

23  Network-Based Approaches for Multi-omics Integration

Index