Online Training

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The PhenoMeNal online training provides researchers a basic understanding about the services, software tools and workflows provided by the PhenoMeNal infrastructure.


LC/MS data analysis with XCMS and MetFrag on PhenoMeNal

In this webinar we will briefly introduce the MetFrag system and then focus on using MetFrag in Galaxy as part of the PhenoMeNal infrastructure.

PhenoMeNal: Metabolomics data analysis in the cloud

In this webinar we will explain the main components of PhenoMeNal. We will demonstrate how to register, access existing tools and workflows, create a new PhenoMeNal CRE on Amazon, and execute a workflow on a PhenoMeNal CRE.

PhenoMeNal: Accessing Metabolomics Workflows in Galaxy

This course will give you an overview of PhenoMeNal, how to create your cloud research environment, and how to access Galaxy workflows for metabolomics data.

How to find and use Galaxy application via the PhenoMeNal portal

This screencast is a tutorial on how to find and use the Galaxy Application via the PhenoMeNal Cloud research Environment Portal. This sub-workflow is part of the Sacurine-statistics workflow available on the W4M e-infrastructure (

The science behind Stable Isotope Resolved Metabolomics (SIRM) used within the Fluxomics Workflow

The objective of the workflow is estimation of metabolic reaction-fluxes by fitting flux-balanced model predictions and experimental mass-spectrometry measurements of 13C propagation from labelled substrates to metabolites.

After finishing the above tutorial, the following video tutorial is “Sacurine workflow demo”, which shows the steps required to run the Sacurine data analysis workflow on the public galaxy instance made available by the PhenoMeNal project at, for registered users.

After finishing the above tutorial, the following tutorial shows the steps required to run the Fluxomics data analysis workflow on PhenoMeNal deployed VRE. This is made available by the PhenoMeNal project for deployment at, for registered users. To try the workflow, please download and unzip first this data to your own machine.