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.

Saved in:
Bibliographic Details
Other Authors Winkler, Robert (Editor)
Format Electronic eBook
LanguageEnglish
Published Cambridge : Royal Society of Chemistry, [2020]
SeriesNew developments in mass spectrometry ; 8.
Subjects
Metabolites > Data processing.
Proteomics > Data processing.
Molecular spectroscopy > Data processing.
Open source software.
elektronické knihy
electronic books
Online AccessFull text
ISBN9781788019880
1788019881
9781788019903
1788019903
9781788017213
1788017218
Physical Description1 online resource

Cover

LEADER 00000cam a2200000 i 4500
001 kn-on1147703771
003 OCoLC
005 20240717213016.0
006 m o d
007 cr cn|||||||||
008 200330s2020 enk o 001 0 eng d
040 |a UKRSC  |b eng  |e rda  |e pn  |c UKRSC  |d UIU  |d UKAHL  |d OCLCF  |d YDX  |d N$T  |d EBLCP  |d UKMGB  |d K6U  |d OCLCO  |d OCLCQ  |d OCLCO  |d UPM  |d LUU  |d OCLCQ  |d PSYSI  |d OCLCQ  |d OCLCO  |d OCLCL 
020 |a 9781788019880  |q (electronic bk.) 
020 |a 1788019881  |q (electronic bk.) 
020 |a 9781788019903  |q (electronic bk.) 
020 |a 1788019903  |q (electronic bk.) 
020 |z 9781788017213 
020 |z 1788017218 
035 |a (OCoLC)1147703771  |z (OCoLC)1145921081 
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. 
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) 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
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 Knovel (All titles) 
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. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
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://proxy.k.utb.cz/login?url=https://app.knovel.com/hotlink/toc/id:kpPMPDOSA4/processing-metabolomics-and?kpromoter=marc  |y Full text 

Similar Items