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- Publisher: MDPI AG
- Year: 2021
- Pages: 276
- ISBN-10: 3036511946
- ISBN-13: 9783036511948
- Format: 17 x 24.4 x 2.2 cm, hardcover
- Language: English
- SAVE -10% with code: EXTRA
Metabolomics Data Processing and Data Analysis-Current Best Practices (e-book) (used book) | bookbook.eu
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Description
Metabolomics data analysis strategies are central to transforming raw metabolomics data files into meaningful biochemical interpretations that answer biological questions or generate novel hypotheses. This book contains a variety of papers from a Special Issue around the theme "Best Practices in Metabolomics Data Analysis". Reviews and strategies for the whole metabolomics pipeline are included, whereas key areas such as metabolite annotation and identification, compound and spectral databases and repositories, and statistical analysis are highlighted in various papers. Altogether, this book contains valuable information for researchers just starting in their metabolomics career as well as those that are more experienced and look for additional knowledge and best practice to complement key parts of their metabolomics workflows.
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- Publisher: MDPI AG
- Year: 2021
- Pages: 276
- ISBN-10: 3036511946
- ISBN-13: 9783036511948
- Format: 17 x 24.4 x 2.2 cm, hardcover
- Language: English English
Metabolomics data analysis strategies are central to transforming raw metabolomics data files into meaningful biochemical interpretations that answer biological questions or generate novel hypotheses. This book contains a variety of papers from a Special Issue around the theme "Best Practices in Metabolomics Data Analysis". Reviews and strategies for the whole metabolomics pipeline are included, whereas key areas such as metabolite annotation and identification, compound and spectral databases and repositories, and statistical analysis are highlighted in various papers. Altogether, this book contains valuable information for researchers just starting in their metabolomics career as well as those that are more experienced and look for additional knowledge and best practice to complement key parts of their metabolomics workflows.
Reviews