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Neuweger, Heiko: MeltDB : a software platform for the analysis and integration of metabolomics experiment data. 2009
Inhalt
List of Figures
List of Tables
Motivation and Overview
Background
Separation and chromatography
Basics of chromatography
Chromatographic systems
Mass spectrometry
Mass spectrometer
Ionization methods
Mass-detection approaches
Mass spectrum
Hyphenated mass spectrometry
Gas chromatography - mass spectrometry (GC-MS)
Liquid chromatography - mass spectrometry (LC-MS)
Capillary electrophoresis - mass spectrometry (CE-MS)
Structure of chromatographic data
Signal processing and feature detection
Chromatogram alignment
Continuous time series alignment
Feature based chromatogram alignment
Compound identification
Mass spectral reference databases
De novo identification of compounds
Mass decomposition
Data analysis strategies for metabolomics datasets
Properties of metabolomics data
Data pre-treatment methods
Explorative data analysis
Machine learning and classification
State of the art in the analysis of metabolomics data
Proprietary and vendor specific systems
Thermo Xcalibur
LECO ChromaTOF
Agilent Mass Hunter
MassLynx
AMDIS
Software from the scientific community
SetupX and BinBase
MZmine
MET-IDEA
MetAlign
XCMS and centWave
TagFinder
MetaboAnalyst
Metabolic pathway repositories and visualization tools
Evaluation of existing systems
Requirements and System Design
System design
Data model
Experiment description
Software as a service
Project management
Access control model
Tool concept
Statistical analysis
Data integration
Implementation and Methods
Supported input formats
Raw data visualization
Experimental overview
User interface
Preprocessing
Implemented Tools
Peak detection
Mass spectral database search
Retention index computation
Compound identification
Support for non-targeted profiling analysis
Feature based chromatogram alignment (FBCA)
Importer
Implemented statistical analysis features
Visualization of PCA and ICA results
Metabolite correlation analysis
Mass decomposition for the identification of metabolites
Manual annotation functionality and user defined References
Data integration
Multi-omics data integration
Web Services and external data integration
Visualization and Animation features
Application examples
Xcc B100 grown on three different carbon sources
Analysis of human heart and blood plasma samples
Variable importance estimation
Analysis of a multi-omics fermentation experiment of Corynebacterium glutamicum
Statistical analysis of cell harvesting methods
Discussion
Conclusion and Outlook
ERT construction & Data model
Abbreviations