Processing Metabolomics and Proteomics Data with Open Software
A Practical Guide
1st Edition
Published on 16. March 2020
430 pages
978-1-78801-990-3 (ISBN)
Description
Metabolomics and proteomics allow deep insights into the chemistry and physiology of biological systems. This book expounds open-source programs, platforms and programming tools for analysing metabolomics and proteomics mass spectrometry data. In contrast to commercial software, open-source software is created by the academic community, which facilitates the direct interaction between users and developers and accelerates the implementation of new concepts and ideas. The first section of the book covers the basics of mass spectrometry, experimental strategies, data operations, the open-source philosophy, metabolomics, proteomics and statistics/ data mining. In the second section, active programmers and users describe available software packages. Included tutorials, datasets and code examples can be used for training and for building custom workflows. Finally, every reader is invited to participate in the open science movement.
More details
Series
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
Product notice
Reflowable
ISBN-13
978-1-78801-990-3 (9781788019903)
DOI
10.1039/9781788019880
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
03/2020
Royal Society of Chemistry
€229.50
Shipment within 3-4 weeks
E-Book
03/2020
1st Edition
Royal Society of Chemistry
€245.99
Available for download
Person
Content
Introduction;
Mass Spectrometry Data Operations and Workflows;
Metabolomics;
Proteomics;
Statistics, Data Mining and Modeling;
OpenMS and KNIME for Mass Spectrometry Data Processing;
Metabolomics Data Analysis Using MZmine;
Pre-processing and Analysis of Metabolomics Data with XCMS/R and XCMS Online;
Statistical Evaluation and Integration of Multi-omics Data with MetaboAnalyst;
Modular metaX Pipeline for Processing Untargeted Metabolomics Data;
Metabolite Annotation With CEU Mass Mediator;
Metabolite Annotation Using In Silico Generated Compounds: MINE and BioTransformer;
Trans-Proteomic Pipeline for the Identification, Validation, and Quantification of Proteins;
Quantitative Proteomics Data Analysis with PANDA, LFAQ and PANDA-view;
Proteomic Workflows with R/R Markdown;
Python in Proteomics;
Mass Spectrometry Development Kit (MSDK): a Java Library for Mass Spectrometry Data Processing;
MASSyPup64: Linux Live System for Mass Spectrometry Data Processing;
Cross-platform Software Development and Distribution with Bioconda and BioContainers;
Concluding Remarks and Perspectives
Mass Spectrometry Data Operations and Workflows;
Metabolomics;
Proteomics;
Statistics, Data Mining and Modeling;
OpenMS and KNIME for Mass Spectrometry Data Processing;
Metabolomics Data Analysis Using MZmine;
Pre-processing and Analysis of Metabolomics Data with XCMS/R and XCMS Online;
Statistical Evaluation and Integration of Multi-omics Data with MetaboAnalyst;
Modular metaX Pipeline for Processing Untargeted Metabolomics Data;
Metabolite Annotation With CEU Mass Mediator;
Metabolite Annotation Using In Silico Generated Compounds: MINE and BioTransformer;
Trans-Proteomic Pipeline for the Identification, Validation, and Quantification of Proteins;
Quantitative Proteomics Data Analysis with PANDA, LFAQ and PANDA-view;
Proteomic Workflows with R/R Markdown;
Python in Proteomics;
Mass Spectrometry Development Kit (MSDK): a Java Library for Mass Spectrometry Data Processing;
MASSyPup64: Linux Live System for Mass Spectrometry Data Processing;
Cross-platform Software Development and Distribution with Bioconda and BioContainers;
Concluding Remarks and Perspectives
