Biochemical Pathways and Large Scale Metabolic Networks

29 August - 2 September 2016

Ioannis Xenarios

Dr Marco Pagni, SIB/UNIL

Kristian Axelsen & Thierry Lombardot, Swiss-Prot & Rhea, SIB: Public databases of metabolites, biochemical reactions and enzymes, web-based and programmatic accesses. Nathan Lewis, University of California San Diego & Andreas Dräger, University of Tübingen: Methods for proper metabolic network reconstruction using BiGG, Escher, and other tools to interact with genome-scale metabolic networks. Jörg Stelling, Computational Systems Biology/SIB & ETHZ: Hybrid Models of Metabolic Networks. Kathrin Fenner, EAWAG and Jörg Wicker, Johannes Gutenberg University Mainz: EnviPath - database and prediction system for the microbial biotransformation of organic environmental contaminants. Marco Pagni, Van Du Tran & Sébastien Moretti, Vital-IT/SIB: The MetaNetX website for genome-scale metabolic network analysis and reconstruction. Usage of R software to analyze and exploit metabolic networks. Christophe Dessimoz, Computational Evolutionary Biology and Genomics, SIB & University of Lausanne: Orthology and Comparative Genomics.

Link to the program

This course and mini-symposium aim at guiding the participants in the complexities of biochemical pathway reconstruction with some emphasis on genome-scale metabolic networks.

• The course consists of selected chapters, which altogether will help the participants to integrate concepts, various data types and different software tools.
• A few practical session will be organised to demonstrate how to build metabolic models and to produce valuable biological knowledge.
• The aim of the mini-symposium is to highlight the current state of research in the field.

University of Lausanne, Genopode building, classroom 2020

Audience

This course is open to everyone, but it is a rather advanced course with a broad scope and hence primarily aimed to PhD students or Postdocs in Biology or Bioinformatics with interest for Systems biology.

Learning objectives

At the end of the course, participants should have a good knowledge or understanding of:

• the current state and the future direction of R&D in the field
• some major public resources (web sites, databases)
• algorithms specific to this field and some of their implementatio

Prerequisites

Knowledge / skills:
People are encouraged to come with their own problem (e.g. their favourite microbes genome or metabolic model). Programming skills or a degree in Biochemistry is not required, but strongly recommended. Basic experience with R is recommended. Material:
Bring a laptop

Free for members of the CUSO/StarOmics program. 200 CHF for academics. Others, please contact us.

Deadline for application and cancellation is set to the 15h of August. Cancellation after this date will not be reimbursed.

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