Workshops > Advanced Data Analysis

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Advanced approaches for the analysis of metabolomics data: From experimental design to knowledge discovery (January 21st 2020, 4pm-6pm.)

Purpose of the workshop:

The objective of this workshop is to introduce key concepts and chemometric methods (experimental strategies, data structures, multivariate models) for the analysis of multifactorial, multiblock and longitudinal metabolomic data. Several examples will be used to illustrate these different aspects.

Intended audience and prerequisites:

- Public: Researchers, engineers or students working in metabolomics and looking for information on data analysis methods and tools dedicated to complex data structures.

- Prerequisites: Basics of metabolomic data analysis.

Skills acquired at the end of the workshop:

- Overall understanding of the different experimental data structures.

- Selection of appropriate chemometric methods to extract knowledge from metabolomic data.


Serge Rudaz & Julien Boccard


  • To register to this workshop please contact:
  • Deadline: decembre 20th 2019
  • Maximun number of attendees: 20


1. Harnessing the complexity of metabolomic data with chemometrics. J. Boccard, S. Rudaz. Journal of Chemometrics (2014), 28(1), 1-9.

2. Exploring Omics data from designed experiments using Analysis of Variance Multiblock Orthogonal Partial Least Squares. J. Boccard, S. Rudaz. Analytica Chimica Acta (2016), 920, 18-28.

3. Integration of metabolomic data from multiple analytical platforms: toward extensive coverage of the metabolome in Data Analysis for Omic Sciences: Methods and Applications, J. Boccard, S. Rudaz. Elsevier (2018).

4. A scoring approach for multi-platform acquisition in metabolomics. J. Pezzatti, V. González-Ruiz, S. Codesido, Y. Gagnebin, A. Joshi, D. Guillarme, J. Schappler, D. Picard, J. Boccard, S. Rudaz. Journal of Chromatography A (2019), 1592, 47-54.


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