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Topic: Introduction to Nutritional Metabolomics (Read 1137 times) previous topic - next topic

Introduction to Nutritional Metabolomics

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Content
The course will provide an introduction to the LC-MS based nutritional metabolomics studies, aiming to cover key steps such as study design, sample collection and analysis, data handling methodologies and metabolite identification.

The students will go through common steps in a typical metabolomics study. Therefore, the major focus will be application of various free or commercial tools for data preprocessing, data analysis, and metabolite identification with computer based hands-on training using example datasets that will be provided to the students.

The course will finalize by presentations of reports generated by the students based on a case study.

SCIENCE, NordFOOD and NUGO homepages only. A limit of 16 participants has been set this year.


Learning outcome
The aim of this course is to introduce the students to all phases in a nutritional metabolomics study and to train the student in the use of available tools for data handling. Both targeted and untargeted LC-MS methodologies will be thought, yet major focus of the course is untargeted LC-MS based metabolomics.

After completing the course the students should be able to:

• Evaluate the effect of study design on data handling and interpretation of final outcome
• Suggest the sample type to analyze for a specific research question and propose the relevant sample collection and preparation procedure 
• Understand the basic principles of LC-MS technology
• Carry out data preprocessing on using freely available tools such as MZmine 
• Perform univariate and multivariate analysis on R/MATLAB 
• Interpret the MS/MS spectra by utilizing available tools (e.g. CAMERA, MetFusion, MetFrag) and databases (e.g. HMDB, MassBank, MZCloud)


Teaching and learning methods
Lectures, hands-on exercises, group discussions.


Lecturers
• Lars O. Dragsted
• Gözde Gürdeniz
• Jan Stanstrup
• Rastislav Monosik
• Mads Vendelbo Lind 


Link: https://phdcourses.ku.dk/DetailKursus.aspx?id=102145&sitepath=NAT
Blog: stanstrup.github.io