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Processing metabolomics and proteomics data with open software : a practical guide /

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.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Winkler, Robert (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge : Royal Society of Chemistry, [2020]
Colección:New developments in mass spectrometry ; 8.
Temas:
Acceso en línea:Texto completo

MARC

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245 0 0 |a Processing metabolomics and proteomics data with open software :  |b a practical guide /  |c edited by Robert Winkler. 
264 1 |a Cambridge :  |b Royal Society of Chemistry,  |c [2020] 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a New developments in mass spectrometry ;  |v 8 
500 |a Includes index. 
588 0 |a Print version record. 
505 0 |a 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 
505 8 |a 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 
505 8 |a 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 
505 8 |a 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 
505 8 |a 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) 
520 |a 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. 
590 |a Knovel  |b ACADEMIC - General Engineering & Project Administration 
650 0 |a Metabolites  |x Data processing. 
650 0 |a Proteomics  |x Data processing. 
650 0 |a Molecular spectroscopy  |x Data processing. 
650 0 |a Open source software. 
650 6 |a Métabolites  |x Informatique. 
650 6 |a Protéomique  |x Informatique. 
650 6 |a Spectroscopie moléculaire  |x Informatique. 
650 6 |a Logiciels libres. 
650 7 |a Molecular spectroscopy  |x Data processing.  |2 fast  |0 (OCoLC)fst01024840 
650 7 |a Open source software.  |2 fast  |0 (OCoLC)fst01046097 
700 1 |a Winkler, Robert,  |e editor. 
776 0 8 |i Print version:  |t Processing metabolomics and proteomics data with open software.  |d Cambridge : Royal Society of Chemistry, 2020  |z 9781788017213  |w (OCoLC)1144801347 
830 0 |a New developments in mass spectrometry ;  |v 8. 
856 4 0 |u https://appknovel.uam.elogim.com/kn/resources/kpPMPDOSA4/toc  |z Texto completo 
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