Details
Processing Metabolomics and Proteomics Data with Open Software
A Practical GuideISSN 1. Aufl.
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239,99 € |
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| Verlag: | Royal Society Of Chemistry |
| Format: | EPUB |
| Veröffentl.: | 16.03.2020 |
| ISBN/EAN: | 9781788019903 |
| Sprache: | englisch |
| Anzahl Seiten: | 430 |
DRM-geschütztes eBook, Sie benötigen z.B. Adobe Digital Editions und eine Adobe ID zum Lesen.
Beschreibungen
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.
Metabolomics and proteomics allow deep insights into the chemistry and physiological processes of biological systems. This book will enable researchers, practitioners and students from different backgrounds to analyze metabolomics and proteomics mass spectrometry data.
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
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