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Metabolomics as a tool in nutrition research /
Metabolomics is a multidisciplinary science used to understand the ways in which nutrients from food are used in the body and how this can be optimised and targeted at specific nutritional needs. Metabolomics as a Tool in Nutrition Research provides a review of the uses of metabolomics in nutritiona...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cambridge, UK :
Woodhead Publishing,
[2015]
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| Edición: | First edition. |
| Colección: | Woodhead Publishing in food science, technology, and nutrition ;
251. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Front Cover; Metabolomics as a Tool in Nutrition Research; Copyright; Contents; List of contributors; Woodhead Publishing Series in Food Science, Technology and Nutrition; Preface; Part One: Principles; Chapter 1: Challenges in nutritional metabolomics: from experimental design to interpretation of data sets; 1.1. Introduction; 1.2. The experimental design; 1.3. The analytical platform; 1.4. Extraction of data sets and statistical analyses; 1.5. Metabolite identification; 1.6. Biological interpretations; 1.7. Conclusion: do we need standardisation procedures and repositories?; References.
- Chapter 2: Metabolic profiling as a tool in nutritional research2.1. Introduction; 2.2. Key issues in nutritional research; 2.3. The role of genomics, proteomics, metabolomics, and metagenomics in nutritional research; 2.4. Applications of metabolomics in nutrition-related research; 2.5. The use of metabolomics to assess the effects of diet on health; 2.5.1. Natural products; 2.5.2. Wheat and fibre; 2.5.3. Meat and fish; 2.5.4. Milk products; 2.5.5. Functional foods; 2.6. Methods for mapping dietary patterns.
- 2.7. Observational and interventional studies into the effects of diet and nutrition on health2.8. Analytical methods; 2.9. Issues in analysing samples; References; Chapter 3: Chemometrics methods for the analysis of genomics, transcriptomics, proteomics, metabolomics, and metagenomics ... ; 3.1. Introduction; 3.2. Unsupervised and supervised pattern recognition methods; 3.3. Multivariate calibration methods for developing predictive models; 3.4. Statistical data integration methods; 3.5. Data integration: multiblock strategies; 3.6. Data integration: calibration transfer methods.
- 3.7. Data integration: multiway/multimodal analysis methods3.7.1. PARAFAC; 3.7.2. Tucker decomposition; 3.8. Data integration: correlation-based approaches; 3.9. Data integration: techniques for analysing different types of genomics datasets; 3.10. Statistical data integration of different sample types; 3.11. Statistical data integration of different molecular components in samples; 3.12. Modelling relationships between molecular components; 3.13. Conclusion and future trends; References; Part Two: Applications in nutrition research; Chapter 4: Application of lipidomics in nutrition research.
- 4.1. Introduction4.2. Lipids; 4.3. Lipidomics; 4.3.1. Sampling and lipid sample preparation; 4.3.2. Lipid analysis; 4.3.2.1. Shotgun lipidomics; 4.3.2.2. LC-MS for lipid analysis; 4.3.3. Data processing and bioinformatics; 4.4. Lipidomics in nutrition research; 4.4.1. Lipidomics in the determination of the effects of specific diets or challenge tests; 4.4.2. Lipidomics in the investigation of metabolic syndrome and associated diseases; 4.4.3. Lipidomics to control food quality; 4.5. Conclusion and future trends; Acknowledgement; References.