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Bioinformatics

Code: SCI3064

Extent: 20 - 25 credits

Language: English

Teacher in charge: Harri Lähdesmäki

Target group:  Students interested in developing and applying computational methods in biological, biomedical and bioeconomy applications. In particular, the minor is designed to complement any major in the Life Science Technologies programme, as well as the major Machine Learning and Data Mining.

Application procedure: The minor is open for all master's students at the Aalto University schools of tehcnology.

Quotas and restrictions: No quotas

Prerequisites: No prerequisites for the minor as a whole, some courses may have their own prerequisites.

 

Content and structure of the minor

The Bioinformatics minor in the Life Science Technologies programme is designed to provide students with competence in bioinformatics and computational systems biology. The minor equips students with skills and tools to develop new computational methods and models and to apply them to real world biomolecular data. Computer practicals are part of most courses ensuring understanding of both theory and practice of the methods. The biological background knowledge can be broadened with an elective minor.

State-of-the-art methods for analysing next-generation sequencing, microarray and other omics data as well as biological networks are part of the curriculum. Examples of research questions studied include predicting drug-target interactions, reconstructing biological networks, finding associations between genotypes and diseases, and modelling dynamical behaviour of complex biological pathways.

Structure of the minor

Code

Name

Credits

Compulsory courses

10

CS-E5860

Computational Genomics

5

CS-E5870

High-throughput Bioinformatics

5

Elective courses

10 - 15

Select as many courses as needed to fulfill the 25-credit requirement

MS-E2115

Experimental and Statistical Methods in Biological Sciences

5

CS-E5880

Modelling Biological Networks

5

CS-E5890

Statistical Genetics and Personalised Medicine

5

CS-E4860

Special Course in Bioinformatics II

 5

CS-E3210

Machine Learning: Basic Principles

 5

CS-E4830

Kernel Methods in Machine Learning

 5

CS-E4820

Machine Learning: Advanced Probabilistic Methods

 5

CS-E4840

Information Visualization

 5

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