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Title Processing metabolomics and proteomics data with open software : a practical guide / edited by Robert Winkler
Published Cambridge : Royal Society of Chemistry, [2020]
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Description 1 online resource
Series New developments in mass spectrometry ; 8
New developments in mass spectrometry ; 8
Contents Intro -- Half Title -- Series editors -- Title -- Copyright -- Preface -- Contents -- Part A General Section -- Chapter 1 Introduction -- 1.1 Hypothesis-driven versus Exploratory Research -- 1.2 Mass Spectrometry Basics -- 1.2.1 The Sample Introduction Unit -- 1.2.2 The Separation/Imaging Component -- 1.2.3 The Ionization Unit -- 1.2.4 The Mass Analyzer -- 1.2.5 Fragmentation -- 1.2.6 Detector -- 1.2.7 Mass Spectra and Mass Chromatograms -- 1.2.8 LC-MS Analysis and Data Acquisition Strategies -- 1.3 Why Open Software for Mass Spectrometry? -- References
3.4 LC-MS Processes and Software for Metabolomics -- 3.4.1 Untargeted LC-MS Metabolomics Tools and Workflows -- 3.4.2 Targeted LC-MS Metabolomics Tools and Workflows -- 3.5 GC-MS Metabolomics Tools and Workflows -- 3.6 CE-MS Metabolomics Workflows and Software -- 3.6.1 Data Pre-processing Software -- 3.6.2 Statistical Analysis -- 3.6.3 Metabolite Annotation -- 3.7 Lipidomics Workflows and Software Tools -- 3.7.1 LC-MS Lipidomics Software -- 3.7.2 Shotgun Lipidomics -- 3.7.3 Imaging Lipidomics of Mass Spectrometry Imaging -- 3.8 Conclusion -- References -- Chapter 4 Proteomics
4.1 The Proteome: Dimensions, Scales, and Complexity -- 4.2 Proteomic Experiments and Data Life Cycle -- 4.3 Signal Processing -- 4.4 Qualitative Analysis -- 4.5 Quantitative Analysis -- 4.6 Getting the Bigger Picture -- References -- Chapter 5 Statistics, Data Mining and Modeling -- 5.1 Sample Comparison -- 5.1.1 Distance Measures -- 5.1.2 Multiple Sample Visualization -- 5.1.3 Outlier Detection -- 5.2 Dimensionality Reduction -- 5.2.1 Principal Component Analysis -- 5.2.2 Self-organizing Maps -- 5.3 Cluster Analyses -- 5.3.1 K-Means -- 5.3.2 Hierarchical Clustering -- 5.4 Important Variables
5.4.1 Ranking Peaks -- 5.4.2 Biomarker Discovery -- 5.5 Predictive Models -- 5.5.1 Machine Learning Introduction -- 5.5.2 Supervised Learning Models -- 5.5.3 Dataset Partitioning Methods -- 5.5.4 Performance Measures -- 5.5.5 A Classification Case Study -- Acknowledgements -- References -- Part B Open MS Programs, Toolkits and Workflow Platforms -- Chapter 6 OpenMS and KNIME for Mass Spectrometry Data Processing -- 6.1 Introduction -- 6.2 OpenMS for Developers -- 6.2.1 C++ Library -- 6.2.2 Data Formats and Raw Data API -- 6.2.3 Algorithms -- 6.2.4 TOPP Tools (Developer Perspective)
Chapter 2 Mass Spectrometry Data Operations and Workflows -- 2.1 Operations -- 2.1.1 Formatting -- 2.1.2 Alignment -- 2.1.3 Peak Detection -- 2.1.4 Identification -- 2.1.5 Calibration -- 2.1.6 Quantification -- 2.1.7 Quality Control -- 2.1.8 Statistical Analysis -- 2.1.9 Visualization -- 2.1.10 Deposition -- 2.2 Workflows -- References -- Chapter 3 Metabolomics -- 3.1 Introduction to Metabolomics -- 3.2 Different 'Flavours' of Metabolomics -- 3.3 Technologies for Metabolomics -- 3.3.1 LC-MS and LC-MS/MS for Metabolomics -- 3.3.2 GC-MS for Metabolomics -- 3.3.3 CE-MS for Metabolomics
Summary 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
Notes Includes index
Print version record
Subject Metabolites -- Data processing
Molecular spectroscopy -- Data processing
Open source software.
Proteomics -- Data processing
Molecular spectroscopy -- Data processing.
Open source software.
Genre/Form Electronic books.
Form Electronic book
Author Winkler, Robert, editor.
ISBN 1788019881
1788019903
9781788019880
9781788019903