Welcome to the MATRIX: Metabolomics Advanced Training and International Exchange Program

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Note: In response to the covid19 pandemic, MATRIX programming has moved online to Slack. Please contact us for an invitation to join the channel if you haven't already done so.

Metabolomics Advanced Training and International Exchange Program (MATRIX) is a collaborative training program supported by Collaborative Research and Training Experience (CREATE) from the Natural Sciences and Engineering Research Council of Canada (NSERC). MATRIX provides leading-edge training in metabolomics, an exciting and rapidly expanding area of research.

Participating Laboratories

MATRIX is an interdisciplinary program, bringing together a core team of experts based at the University of Ottawa, Université de Montréal, and McGill University, in collaboration with our international and academic partners.

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Program Outline

MATRIX is aimed at training the next great MSc and PhD students, by providing a unique wet-to-dry bench immersion in all aspects of metabolomics.

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Program Requirements

MATRIX is training the next generation of leaders for customized career paths in the field of metabolomics, bioenergetics and bioinformatics, in preparation for industrial and academic applications. See how you can join us.

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What is Metabolomics?

Metabolomics is the simultaneous measurement of an as-yet unquantified number of individual metabolites, using a combination of biochemistry, mass spectrometry (MS), nuclear magnetic resonance (NMR) and computer science (data processing, statistics, and network mapping).

Why train with MATRIX?

1) Metabolism has a MAJOR and underappreciated influence on biological functions, including growth and differentiation, epigenetics, bioenergetics and cell death.

2) NOT ALL of the important metabolic pathways have been discovered.

3) The range of metabolites that can be unambiguously defined is NOT restricted to those that can be easily assayed by simpler approaches.

4) Like all `omics’ fields, metabolomics comes with a truly unique set of theoretical and practical challenges.

5) The national and global market for metabolomics researchers is rapidly expanding.

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Can we make ion mobility (LC-ESI-DMS-MS/MS) easier? @MMetabolomics #NRLLab @mlaval6 & Dr Ted Perkins #bioengineering student Xun Xun Shi presenting a machine learning neural net that predicts @SCIEXOmics differential mobility spectrometry SVs and COVs for all cerebrosides.

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Please consider joining Dr. Julie St-Pierre (@uOttawa) and @Lyssiotislab for a seminar on "Application/integration of metabolomics and Seahorse XF to study tumor and immune metabolism", sponsored by @Agilent. Registration is free 👍🏼, link below.

https://seahorseinfo.agilent.com/acton/fs/blocks/showLandingPage/a/10967/p/p-029c/t/page/fm/0

I am looking for awesome graduate students to take on exciting projects on mitophagy in muscle stem cells. Check out this opportunity at https://neuromuscularnetwork.ca/opportunity/graduate-student-position-burelle-lab/

In order to get the most out of your data, always run calculations AND graphs! Why you ask? In this example, the different graphs have basically the same summary statistics! (Part of what I learned today @WCMC_UCDavis)

Take a closer look:

https://www.autodesk.com/research/publications/same-stats-different-graphs

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