Computational Methods and Data Analysis for Metabolomics
| Körperschaft: | |
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| Weitere Verfasser: | |
| Zusammenfassung: | XI, 491 p. 175 illus., 119 illus. in color. text |
| Sprache: | Englisch |
| Veröffentlicht: |
New York, NY :
Springer US : Imprint: Humana,
2020.
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| Ausgabe: | 1st ed. 2020. |
| Schriftenreihe: | Methods in Molecular Biology,
2104 |
| Schlagworte: | |
| Online-Zugang: | https://doi.org/10.1007/978-1-0716-0239-3 |
| Format: | Elektronisch E-Book |
Inhaltsangabe:
- Overview of Experimental Methods and Study Design in Metabolomics, and Statistical and Pathway Considerations
- Metabolomics Data Processing using XCMS
- Metabolomics Data Preprocessing using ADAP and MZmine 2
- Metabolomics Data Processing using OpenMS
- Analysis of NMR Metabolomics Data
- Key Concepts Surrounding Studies of Stable Isotope Resolved Metabolomics
- Extracting Biological Insight from Untargeted Lipidomics Data
- Overview of Tandem Mass Spectral and Metabolite Databases for Metabolite Identification in Metabolomics
- METLIN: A Metabolite Mass Spectral Database
- Metabolomic Data Exploration and Analysis with the Human Metabolome Database
- De Novo Molecular Formula Annotation and Structure Elucidation using SIRIUS 4
- Annotation of Specialized Metabolites from High-throughput and High-resolution Mass Spectrometry Metabolomics
- Feature Based Molecular Networking for Metabolite Annotation. A Bioinformatics Primer to Data Science, with Examples for Metabolomics
- The Essential Toolbox of Data Science: Python, R, Git and Docker
- Predictive Modeling for Metabolomics Data
- Using MetaboAnalyst 4.0 for Metabolomics Data Analysis, Interpretation, and Integration with Other Omics Data
- Using Genome Scale Metabolic Networks for Analysis, Visualization, and Integration of Targeted Metabolomics Data
- Pathway Analysis for Targeted and Untargeted Metabolomics
- Application of Metabolomics to Renal and Cardiometabolic Diseases
- Using the IDEOM Workflow for LCMS-Based Metabolomics Studies of Drug Mechanisms
- Analyzing Metabolomics Data for Environmental Health and Exposome Research
- Network-based Approaches for Multi-omics Integration. .