Preliminary course schedule for 2018/2019 (bottom of page)

The Master´s programme comprises of 120 credits and it is possible to complete the degree in two years, in accordance with an approved personal study plan. The degree includes

85 cr of advanced courses, including

  • shared courses within the programme
  • study track specific courses within the programme
  • the Master’s thesis, 30 cr
  • thesis seminar which includes study orientation 5 cr

35 cr of other courses from your own or other programmes,

The programme gives introductory courses from all six study tracks and you should choose at least three of these courses. You should be ready to choose your own study track after studying one or two study periods. Study tracks provide several alternative courses. Most courses comprise 5 credits and most courses will be in study programme every other year; the introductory course will be given annually.

  • Applied bioinformatics: 

Contact person: Ville Mustonen
Introduction to Applied Bioinformatics (introductory course)
Practical course in genome bioinformatics
Protein informatics
Evolutionary Genomics
Next Generation Genomics
Introduction to Evolutionary Ecological Genomics
Gene mapping
Project work
Courses from the MSc programme in Genetics and Molecular Biosciences. 

  • Algorithmic bioinformatics

Contact person: Veli Mäkinen
Algorithms for bioinformatics (introductory course)
at least 10 cr from the following courses:
Biological sequence analysis
Algorithms in molecular biology
Research seminar in algorithmic bioinformatics
at least 10 cr courses from the Msc programme of Computer science, study track algorithms:
Algorithm design and analysis
Introduction to machine Learning
String processing algorithms
Other suitable algorithm courses as agreed in FM-HOPS
Courses from other study tracks in Life Science Informatics MSc programme

  • Biomathematics

Contact person: Mats Gyllenberg
Mathematical modelling (introductory course)
Introduction to mathematical biology (an alternative introductory course)
Adaptive dynamics
Evolution and the theory of games
Stochastic population models
Spatial models in ecology and evolution
Mathematics of infectious diseases

  • Biostatistics and bioinformatics

Contact person: Sirkka-Liisa Varvio
Trends on biostatistics and bioinformatics (introductory course)
Phylogenetic inference and data analysis
Statiatistical population genetics
Modelling molecular evolution
Genome-wide association studies
Courses from other study tracks in Life Science Informatics MSc programme, especially from the study track Algorithmic bioinformatics
Courses from the MSc programme Mathematics and statistics, especially:
Computational statistics
Bayesian data-analysis
High dimensional statistics
Spatial statistics

  • Eco-evolutionary informatics

Contact person: Jarno Vanhatalo
Modelling ecology and evolution (introductory course)
At least 10 credits from the MSc programme Mathematics and statistics courses and/or Biomathematics Life Science Infromatics study track courses:
Bayesian inference in biosciences
Spatial modelling and Bayesian statistics
Introduction to mathematical biology
Mathematical modelling
Other courses from Biomathematics study track and /or other Msc programmes:
Spatial models in ecology and evolution
Mathematics of infectious diseases
Stochastic population models
Population assessment for environmental management
Project work in eco-evolutionary informatics
Courses from the MSc programme Ecology and evolutionary biology, as agreed in the personal-HOPS

  • Systems biology and medicine

Contact person: Sampsa Hautaniemi
Introduction to systems biology (introductory course)
Clinical data mining
Basics of clinical investigation
Courses from other Life Science Informatics study tracks and other MSc programmes, especially from the Computer science programme and Translational Medicine programme