Li | Computational Methods and Data Analysis for Metabolomics | Buch | 978-1-0716-0238-6 | sack.de

Buch, Englisch, 491 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1136 g

Reihe: Methods in Molecular Biology

Li

Computational Methods and Data Analysis for Metabolomics


1. Auflage 2020
ISBN: 978-1-0716-0238-6
Verlag: Springer US

Buch, Englisch, 491 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1136 g

Reihe: Methods in Molecular Biology

ISBN: 978-1-0716-0238-6
Verlag: Springer US


This book provides a comprehensive guide to scientists, engineers, and students that employ metabolomics in their work, with an emphasis on the understanding and interpretation of the data. Chapters guide readers through common tools for data processing, using database resources, major techniques in data analysis, and integration with other data types and specific scientific domains. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, practical guidance of methods and techniques, useful web supplements, and connect the steps from experimental metabolomics to scientific discoveries.

Authoritative and cutting-edge, Computational Methods and Data Analysis for Metabolomics to ensure successful results in the further study of this vital field.

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Weitere Infos & Material


1. Overview of Experimental Methods and Study Design in Metabolomics, and Statistical and Pathway Considerations

Stephen Barnes

2. Metabolomics Data Processing using XCMS

Xavier Domingo-Almenara and Gary Siuzdak

3. Metabolomics Data Preprocessing using ADAP and MZmine 2

Xiuxia Du, Aleksandr Smirnov, Tomáš Pluskal, Wei Jia, and Susan Sumner

4. Metabolomics Data Processing using OpenMS

Marc Rurik, Oliver Alka, Fabian Aicheler, and Oliver Kohlbacher

5. Analysis of NMR Metabolomics Data 

Wimal Pathmasiri, Kristine Kay, Susan McRitchie, and Susan Sumner

6. Key Concepts Surrounding Studies of Stable Isotope Resolved Metabolomics

Stephen F. Previs and Daniel P. Downes

7. Extracting Biological Insight from Untargeted Lipidomics Data

Jennifer E. Kyle

 

8. Overview of Tandem Mass Spectral and Metabolite Databases for Metabolite Identification in Metabolomics

Zhangtao Yi and Zheng-Jiang Zhu

9. METLIN: A Metabolite Mass Spectral Database

J. Rafael Montenegro-Burke, Carlos Guijas, and Gary Siuzdak

10. Metabolomic Data Exploration and Analysis with the Human Metabolome Database

David S. Wishart

11. De Novo Molecular Formula Annotation and Structure Elucidation using SIRIUS 4

Marcus Ludwig, Markus Fleischauer, Kai Dührkop, Martin A. Hoffmann, and Sebastian Böcker

12. Annotation of Specialized Metabolites from High-throughput and High-resolution Mass Spectrometry Metabolomics

Thomas Naake, Emmanuel Gaquerel, and Alisdair R. Fernie

13. Feature Based Molecular Networking for Metabolite Annotation

Vanessa V. Phelan

14. A Bioinformatics Primer to Data Science, with Examples for Metabolomics

W. Stephen Pittard, Cecilia “Keeko” Villaveces, and Shuzhao Li

15. The Essential Toolbox of Data Science: Python, R, Git and Docker

W. Stephen Pittard and Shuzhao Li

16. Predictive Modeling for Metabolomics Data

Tusharkanti Ghosh, Weiming Zhang, Debashis Ghosh, and Katerina Kechris

17. Using MetaboAnalyst 4.0 for Metabolomics Data Analysis, Interpretation, and Integration with Other Omics Data

Jasmine Chong and Jianguo Xia

18. Using Genome Scale Metabolic Networks for Analysis, Visualization, and Integration of Targeted Metabolomics Data

Jake P. N. Hattwell, Janna Hastings, Olivia Casanueva, Horst Joachim Schirra, and Michael Witting

19. Pathway Analysis for Targeted and Untargeted Metabolomics

Alla Karnovsky and Shuzhao Li

 

20. Application of Metabolomics to Renal and Cardiometabolic Diseases

Casey M. Rebholzand Eugene P. Rhee

21. Using the IDEOM Workflow for LCMS-Based Metabolomics Studies of Drug Mechanisms

Anubhav Srivastavaand Darren J Creek

  22. Analyzing Metabolomics Data for Environmental Health and Exposome Research

Yuping Cai, Ana Rosen Vollmar, and Caroline Helen Johnson

23. Network-based Approaches for Multi-omics Integration

Guangyan Zhou, Shuzhao Li, and Jianguo Xia



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