Molpage Training


Statistical Analysis of Metabonomic and Proteomic Data		MolPAGE

Luisa Bernardinelli	Introduction
Richard Barton	Introduction to metabonomics: principles and historical perspectives
Anthony Maher	NMR data in Metabonomics
Cinzia Stella	Specificity of MS-based metabonomic data
Richard Barton	Overview - Basic Pattern Recognition
Mark Earll Richard Barton Marc-Emmanuel Dumas	Introduction to Multivariate Projection Methods
Mark Earll	Validation of Multivariate Methods and Robustness
Mark Earll	Demonstration of a simple PCA using the 'FOODS' dataset
Marc-Emmanuel Dumas	Practical aspects of NMR data processing
Magnus Åberg	Alignment and Warping - Solving the correspondence problem for metabonomics data sets
Marc-Emmanuel Dumas	Metabonomics as a Driving Force in Post-Genomic Data Integration
Mattias Rantalainen	Multivariate approaches to integration of Metabonomic and Proteomic data
Paul Eilers	Data collection and analysis for high-throughput quantitative proteomics: current status and challenges
Paul Eilers	Experimental design, measurement errors and data transformation for Proteomics and Metabonomics data
Nathan Edwards	Statistical significance for peptide identification by tandem mass spectrometry
Ingileif Hallgrimsdottir George Nicholson	Lessons from MolPAGE on analysis of proteomics and metabonomics data on the same samples
Ingileif Hallgrimsdottir George Nicholson	Practicals at computer on analysis of proteomics and metabonomics data
Arief Gusnanto	Multiple comparison issues and False Discovery Rate
Paul Eilers	Statistical Modelling of mass spectrometry proteomic data
Bart Mertens	Case-control study design and validation-based modelling for pattern classification in proteomics mass spectral data
Carlo Berzuini	Causal modelling in functional genomics
Chris Holmes	Bayesian methods for detecting genetical biomarkers in NMR and Mass Spectrometry data
Bernard Silverman	Empirical Bayes thresholding:adapting to sparsity when it is advantageous to do so
Philip Brown	Bayesian Modelling and Feature Selection of Proteomic Functional Data
Jens Lamerz	Quantitative Approaches in Proteomics
Carlo Berzuini	Closure