This second editing provides new and updated methods on metabolomics software and tool universe. Chapters guide readers through data processing, database resources, major techniques in data analysis, and integration with other data types and specific scientific domains. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, practical guidance of methods and techniques, useful web supplements, and connect the steps from experimental metabolomics to scientific discoveries.

Authoritative and cutting-edge, Computational Methods and Data Analysis for Metabolomics, Second Edition aims to ensure successful results in the further study of this vital field.

Chapter 3 is available open access under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License via link.springer.com.

Includes cutting-edge methods and protocols Provides step-by-step detail essential for reproducible results Contains key notes and implementation advice from the experts

Inhalt

Practicing data science in interactive notebooks.- LC-MS data processing using xcms.- mzmine: Unifying Mass Spectrometry Data Processing.- LC-MS data processing using OpenMS.- Metabolomics Data Processing using the Asari Toolkit.- LC-MS/MS-based untargeted lipidomics using MS-DIAL.- LC-MS/MS-based untargeted hydrophilic metabolomics using MS-DIAL.- Computational Tools for LCIMSMS Data Processing in Metabolomics.- Tandem mass spectral databases and their use in non-targeted metabolomics.- Metabolite annotation and identification in R.- Large-scale Metabolite Annotation in Untargeted Metabolomics Using MetDNA.- Lipid and metabolite annotation using Lipid Data Analyzer.- Prediction, targeting and annotation of oxidized lipids using LPPtiger2 software.- Comprehensive LC-MS metabolomics data processing with notame R/Bioconductor package.- Metabolomics data analysis with TIGER.- Metabolomics spectral processing, data analysis, and multi-omics integration using MetaboAnalyst 6.0.- Multi-omics guided pathway and network analysis of clinical metabolomics and proteomics data.- Metabolomics Data Analysis With The HMDB.