Computational Biology, intermediate studies as elective studies, 20 op

Opintokokonaisuuden tyyppi

Intermediate Studies


Frank Emmert-Streib, Olli Yli-Harja, Juha Kesseli


- Have basic knowledge of Cell and Molecular Biology, Biotechnology, Signal and Image Processing.
- Implement models of biological systems.
- List and describe the main research areas of Computational Biology.
- Provide examples of how computational models are used in the study of biological systems.
- Use computational tools, such as Matlab or R, to implement and solve problems in biological data analysis, such as image and data analysis.


Pakolliset opintojaksot

Opintojakso Opintopisteet Vuosikurssi
BMT-51016 Introduction to Cell and Molecular Biology 5 op V  
BMT-56008 Laboratory course in Computational Biology 5 op V  
SGN-54106 Computational Diagnostics 5 op V  
Yhteensä 15 op  

Pakolliset vaihtoehtoiset opintojaksot

Students are advised to select from the list of optional courses, one of the following courses.

Must be selected at least 5 credits of courses

Opintojakso Opintopisteet Vuosikurssi
BMT-52606 Processing of Biosignals 5 op IV  
BMT-53507 Cell Imaging and Signal Processing 5 op V  
SGN-11007 Introduction to Signal Processing 5 op II  
SGN-12007 Introduction to Image and Video Processing 5 op III  
SGN-13006 Introduction to Pattern Recognition and Machine Learning 5 op III  


The Minor in Computational Biology provides knowledge on how to design and implement models of biological systems. Also, it teaches how to use computational tools for biological data analysis.

The Minor in Computational Biology is a valuable, complementary knowledge for students of Signal Processing and Software Engineering that aim to apply their efforts to study biological/medical topics as well as for students of biological/biotechnological/medical degrees that aim to perform modeling of biological systems or make use of computational methods, e.g. from Signal Processing, such as image and statistical analysis.

The Minor in Computational Biology is highly multi-disciplinary in that it provides knowledge in Computational Biology, along with knowledge from the areas of Signal Processing, Machine Learning and Experimental Biology..

Contact person: Olli Yli-Harja

Only intended as a minor

Päivittäjä: Korpela Anjariitta, 08.04.2019