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NMR Metabolomics in Cancer Research
Miroslava ?uperlovi?-Culf (Author)
9781907568848, Elsevier Science
Hardback, published 17 December 2012
446 pages
23.3 x 15.6 x 2.8 cm, 0.81 kg
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.
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
