Advanced Proteomics and Metabolomics


Course Objectives:

  1. To provide students with a fundamental understanding of mass spectrometry-based data acquisition techniques for proteomics and metabolomics.

  2. To introduce students to advanced mass spectrometry-based data analysis techniques for proteomics and metabolomics.

  3. To equip students with the ability to interpret and analyze proteomics and metabolomics data sets using computational tools.

  4. To teach students how to apply statistical methods to proteomics and metabolomics data analysis to identify significant changes in protein and metabolite expression.

  5. To train students on how to perform data processing and analysis for various types of mass spectrometry-based experiments, such as label-free and isobaric labeling approaches.

  6. To provide students with an understanding of the biological significance of the data generated from mass spectrometry-based experiments and how to interpret the results.

  7. To enable students to understand how mass spectrometry can pin point post translations modification.

  8. To prepare students to design and implement mass spectrometry-based experiments and analyze the resulting data in order to answer biological questions in proteomics and metabolomics.

  9. To enable students to critically evaluate published proteomics and metabolomics data and assess their relevance to specific research questions.

Overall, the course strives to provide students an improved comprehension of the biological context in which the data are produced, as well as the technical knowledge and practical skills required for effective mass spectrometry-based data analysis in proteomics and metabolomics.

General characterization





Responsible teacher

Rune Matthiesen


Weekly - 4

Total - 30

Teaching language



Recommended requirements not necessarily mandatory:


A Bachelor''s degree in a relevant field such as biochemistry, molecular biology, biotechnology, chemistry, or a related discipline.

  1. Prior coursework in bioinformatics, mass spectrometry principles, protein biochemistry and protein separation techniques.

  2. Basic knowledge of statistics, including hypothesis testing, regression analysis, and experimental design.

  3. Familiarity with programming languages such as R or Python, including data visualization and statistical analysis tools.





Teaching method

Available soon

Evaluation method

Available soon

Subject matter

From 9.30 AM to 2 PM.

May 2nd

(Room E-1.01, NOVA medical school main building)
Database dependent searches
9.30-12.00 P: Overview of MS-based proteomics applications
9.30-12.00 P: Database dependent searches

12.30-14.00 TP: MaxQuant and SearchGui, FDR

12.30-14.00 TP: Peak processing, de novo sequencing

May 9th
(In ITQB room 3.20) UniMS proteomics. Lecture and practical session more focused on instrumentation.
Fundamentals of proteomics (Profs. Isabel Abreu, Ricardo Gomes, Bruno Alexandre)
May 16th
(In ITQB room 3.20) UniMS metabolomics. Lecture and practical session more focused on instrumentation.
Fundamentals of metabolomics (Profs. Luís Gonçalves, Ana Guerreiro)

May 23th
Holiday no class

May 30th
(Room E-1.01, NOVA medical school main building)
Quantitative proteomics
9.30-12.00 P: Overview of quantitative methods
12.30-14.00 TP: Label free and stable isotope labeling based quantitation

June 6th  
(Room E-1.01, NOVA medical school main building)
Post translational modifications (PTMs)
9.30-12.00 P: Overview of post translation modification analysis
12.30-14.00 TP: Phospho proteomics analysis

June 14th
(Room TBA 9.00-12.00)
Written test