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Topic: EMBO Practical Course on Metabolomics Bioinformatics for Life Scientists 2018 (Read 239 times) previous topic - next topic

  • Reza Salek
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EMBO Practical Course on Metabolomics Bioinformatics for Life Scientists 2018
EMBO Practical Course on Metabolomics Bioinformatics for Life Scientists

Date:  Monday 5 - Friday 9 February 2018
Venue:  European Bioinformatics Institute (EMBL-EBI) - Wellcome Genome Campus, Hinxton, Cambridge,  CB10 1SD, United Kingdom
Application deadline:  Friday, November 03 2017

Contact: Reza Salek (reza.salek@ebi.ac.uk)
Registration: https://www.ebi.ac.uk/training/events/2018/embo-practical-course-metabolomics-bioinformatics-life-scientists-4

Overview

This course will provide an overview of key issues that affect metabolomics studies, handling datasets and procedures for the analysis of metabolomics data using bioinformatics tools. It will be delivered using a mixture of lectures, computer-based practical sessions and interactive discussions. The course will provide a platform for discussion of the key questions and challenges in the field of metabolomics, from study design to metabolite identification. We encourage you to bring your data, data problems you might have with a particular data set or study for group discussion and activities.  You will be asked to present your work and participate in the discussions from day one.

Audience
This course is aimed at PhD students, post-docs and researchers with at least one to two years of experience in the field of metabolomics who are seeking to improve their skills in metabolomics data analysis.

seeking to improve their skills in metabolomics data analysis. 

Syllabus, tools and resources

 • Metabolomics study design, workflows and sources of experimental error, difference between target and un-target approaches
• Metabolomics data processing tools: hands on open source R based programs, XCMS, MetFrag, MetFusion, rNMR, BATMAN
• Metabolomics data analysis: Using R Bioconductor, understanding usage of univariate and multivariate data analysis, data fusion concepts, data clustering and regression methods
• Metabolomics downstream analyses: KEGG, BioCyc, and MetExplore for metabolic pathway and network analysis with visualisation of differential expression, understanding metabolomics flux analysis
• Metabolomics standards and databases: data dissemination and deposition in EMBL- EBI MetaboLights repository; PheNoMeNal, workflows4metabolomics
• Metabolomics Flux and Stable Isotope Resolved Metabolomics (SIRM)
  • Last Edit: September 22, 2017, 03:34:41 AM by Reza Salek