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Computational Systems Biology

HUT / Lab. of Computational Engineering
Acad. prof Kimmo Kaski
Dr.Tech. Aki Vehtari


Computational systems biology major familiarizes students with the basics of bio-systems especially their molecular, cellular and tissue level structures and processes, and with the mathematical modeling and data-analysis of these systems including the development of computational methods and information processing techniques.

With the break-through in deciphering the human genome using the most up-to-date computational approaches and modern experimental biotechnology, it has become possible to understand the structure and functions of bio-molecules, information stored in DNA (bioinformatics), its expression to proteins, protein structures (proteomics), metabolic pathways and networks, intra- and inter-cell signaling, and the physico-chemical mechanisms involved in them (biophysics).

Using the computational methods in conjunction with the collected geno- and pheno-type data, it seems possible to influence national health sector, e.g. for preventive medicine. Generally speaking, computational systems biology education focuses either on information processing of biological data or on modeling physical and chemical processes of bio-systems, both of which play nowadays central role in modern medicine, gene technology, and pharmaceutical and other biotechnology fields.

The central aim of computational systems biology major is to train all-around experts, for research, education, development, design and consulting jobs, which in the public sector would include national health, research and university institutions, and in the private sector pharmaceutical, service type bioinformatics & bio-computing and other biotechnology companies, and increasingly also in other information technology firms. This major is well suited for M.Sc. and Ph.D. studies due to large number of courses being given in English at this level.

Structure of the Major / Minor

Obligatory studies
S-114.100 Computational Science* (3 cr)
S-114.310 Introduction to Modelling and Information Theory (2 cr)
S-114.500 Basics for Biosystems of the Cell* (3 cr)
S-114.510 Computational Systems Biology (3 cr)
Choose from the following list to get total 20 cr
S-114.200 Special Course of Computational Engineering I (4 cr) L
S-114.230 Individual Studies on Computational Engineering (1-6 cr) LV
S-114.250 Special Topics in Computational Science (4 cr) L
S-114.260 Molecular Modelling (4-6 cr) L
S-114.270 Computational Cell Biology (3-6 cr)
S-114.520 Special Project in Computational Systems Biology (2-5 cr) L
S-114.600 Introduction to Bayesian Modelling (2 cr)
S-72.343 / T-79.165 Graph Theory (3 cr)
S-72.340 Information Theory (3 cr)
S-88.200 Statistical Signal Processing (3 cr)
T-61.246 Digital Signal Processing and Filtering (4 cr)
T-79.161 Combinatorial Algorithms (2 cr) L
T-106.253 Data Structures and Algorithms Y (3-5 cr)
Mat-2.103 Design of Experiments and Statistical Models (2,5 cr)
Mat-2.104 Introduction to Statistical Inference (2,5 cr) L
Mat-2.111 Stochastic Processes (3 cr) L
Mat-2.112 Statistical Multivariate Methods (2-4 cr) L
Tfy-3.363 Introduction to Soft Matter Physics (3 cr) L
Tfy-3.364 Statistical Physics and Thermodynamics (4,5 cr) L
Tfy-99.262 Living State Physics I (Biophysics) (3 cr)
Tfy-99.264 Living State Physics III (Molecular Biophysics) (3 cr) L
Kem-30.326 Medical Microbiology (4 cr)
Kem-30.501 Methods in Molecular Biology and Genetics Engineering (2 cr)
Kem-31.500 / Kem-30.500 Biochemistry, Biophysical Chemistry and Bioenergetics (4 cr)
Kem-70.550 Bioprocesses (2 cr)
Kem-70.552 Bioprocess and Metabolic Modelling (4 cr)

* Needs to be included in the major, unless it is already included into the first part studies or into the orientating studies

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This page has been updated 24.11.2005