Bioinformatics course for Mass Spectrometric data analysis


The Finnish Proteomics society, FinnProt, arranges a two-day Bioinformatics course in Biomedicum 1, Helsinki. The course will provide both theoretical and practical training in the use of bioinformatics and statistics tools for mass spectrometric data analysis, with a special focus on proteomics. Participants will get familiarized with the data analysis workflow, starting from the experimental design to functional data analysis. The course comprises both theoretical lectures and hands-on training in computer lab, where participants will be trained in the use of bioinformatics tools.


This course is aimed at MSc and PhD level students, as well as researchers who want to get a better understanding of bioinformatics and statistical methods, and gain experience in functional bioinformatics data interpretation. To enter the course a basic understanding of mass spectrometry-based proteomics is beneficial.

Schedule [Please note the venue change]

  • 16.3.2017 at 10-17   SEMINAR ROOM 3, P-floor [60 seats]
  • 17.3.2017
    • 9-11       HAARTMAN Institute, LECTURE HALL 2, P-floor [95 seats]
    • 11-17     SEMINAR ROOM 1-2, P-floor [60 seats]

For the hands on part a personal laptop is required

Registration and participation

The course is open to all academic researches and students. Number of participants is limited to 60.
Please register at: until March 12th, 2017.

The Oodi code for the course is 921257. Participants will obtain 0.5 ECTS (lectures) + 1 ECTS (practical session)


Course will cover:

  • The basics of experimental design,
  • Mass-spectrometry normalization strategies,
  • Principles of statistical tools for MS data analysis,
  • Available tools for MS data interpretation,
  • Tools for functional analysis and data visualization.

 After this course you will be able to:

  • Design your proteomic study,
  • Evaluate the quality of proteomic data sets,
  • Select the appropriate workflow and  software tools for MS data analysis,
  • Easier publish your proteomics data,
  • Get the most out of your proteomic data.

This course is supported by the Doctoral Programme in Biomedicine (DPBM)

Contact info: Maciej Lalowski, and Giulio Calza,