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NMR Metabolomics in Cancer Research
1st Edition - December 17, 2012
Author: Miroslava Čuperlović-Culf
Hardback ISBN:
9 7 8 - 1 - 9 0 7 5 6 8 - 8 4 - 8
eBook ISBN:
9 7 8 - 1 - 9 0 8 8 1 8 - 2 6 - 3
The application of nuclear magnetic resonance (NMR) metabolomics in cancer research requires an understanding of the many possibilities that NMR metabolomics can offer, as well as… Read more
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The application of nuclear magnetic resonance (NMR) metabolomics in cancer research requires an understanding of the many possibilities that NMR metabolomics can offer, as well as of the specific characteristics of the cancer metabolic phenotype and the open questions in cancer research. NMR metabolomics in cancer research presents a detailed account of the NMR spectroscopy methods applied to metabolomics mixture analysis along with a discussion of their advantages and disadvantages. Following an overview of the potential use of NMR metabolomics in cancer research, the book begins with an examination of the cancer metabolic phenotype and experimental methodology, before moving on to cover data pre-processing and data analysis. Chapters in the latter part of the book look at dynamic metabolic profiling, biomarker discovery, and the application of NMR metabolomics for different types of cancer, before a concluding chapter discusses future perspectives in the field.
- Focused description of NMR spectroscopy needed by cancer biologists who are starting to use metabolomics
- Current overview of knowledge related to the cancer metabolic phenotype from the perspective of metabolomics applications
- Information about the best practices in NMR metabolomics experimentation and data preprocessing as applied to different sample types
Researchers or graduate students starting to do metabolomics either from the perspective of cancer biology or medicine, NMR spectroscopy or data analysis; Researchers in academic, industry or government settings
List of figures
List of tables
Abbreviations
About the author
Chapter 1: Introduction
Abstract:
1.1 Possibilities of NMR metabolomics in cancer research
Chapter 2: Biology – cancer metabolic phenotype
Abstract:
2.1 Cancer metabolic phenotype
2.2 Drugs aimed at cancer metabolic phenotype
Chapter 3: Experimental methodology
Abstract:
3.1 Fundamentals of NMR spectroscopy
3.2 1D NMR in mixture analysis
3.3 Multidimensional NMR in metabolomics
3.4 Arrayed NMR experiments
3.5 Isotope labeling for NMR analysis
3.6 Diagnostic magnetic resonance tools based on cancer metabolic phenotype and cancer-induced metabolic changes
Chapter 4: Metabolomics NMR data preprocessing – analysis of individual spectrum
Abstract:
4.1 NMR spectrum preprocessing
4.2 Qualitative metabolomics
4.3 STOCSY
4.4 Quantitative metabolomics
4.5 Novel metabolite structure analysis
Chapter 5: Metabolomics data analysis – processing and analysis of a dataset
Abstract:
5.1 Normalization and scaling
5.2 Biases and confounders in metabolomics
5.3 Data analysis
5.4 Data integration – polyomics analysis
Chapter 6: Dynamic metabolic profiling and metabolite network and pathways modeling
Abstract:
6.1 Dynamic metabolic data analysis
6.2 Computational models of metabolic networks
Chapter 7: Biomarker discovery
Abstract:
7.1 Feature (biomarkers) selection
7.2 Validation of results in supervised analysis
Chapter 8: NMR metabolomics application by cancer type
Abstract:
8.1 Breast cancer
8.2 Brain cancers
8.3 Lung cancer metabolomics analysis and results
8.4 Metabolomics analysis of biofluids in cancer research
Chapter 9: Perspectives
Index
- No. of pages: 446
- Language: English
- Published: December 17, 2012
- Imprint: Woodhead Publishing
- Hardback ISBN: 9781907568848
- eBook ISBN: 9781908818263
MČ
Miroslava Čuperlović-Culf
Dr Miroslava Cuperlovic-Culf is a Research Officer at the National Research Council of Canada Institute for Information Technology, an Adjunct Professor of Chemistry at Mount Allison University and an Adjunct Researcher at the Atlantic Cancer Research Institute. She has a range of publications and patents resulting from research in NMR spectral analysis and modelling, bioinformatics data analysis and computational biology for cellular pathway modelling, as applied to cancer research.
Affiliations and expertise
National Research Council of Canada Institute for Information Technology, Canada