Uusi opinto-opas (sisältäen myös opetusohjelmat) lukuvuodelle 2018-2019 sijaitsee osoitteessa https://opas.peppi.utu.fi . Tältä sivustolta löytyvät enää vanhat opinto-oppaat ja opetusohjelmat.

The new study guide (incl. teaching schedules) for academic year 2018-2019 can be found at https://studyguide.utu.fi. This site contains only previous years' guides.

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Archived Curricula Guide 2013–2014
Curricula Guide is archieved. Please refer to current Curricula Guides
BIOI4370 Advanced Data Analysis of Biomedical Problems 4 ECTS
Organised by
Person in charge
Sebastian Okser
Preceding studies
Knowledge of R, Python, basics of statistics.

Learning outcomes

To advance on the data analysis skills acquired in other courses. Through practical work attendees will be given the opportunity to apply programming, mathematics and knowledge of biological systems to develop solutions to real world problems and gain an understanding of practical applications of bioinformatics.


Introduction to the analysis of biomedical datasets through the use of various programming languages. Addressing issues of dimensionality of datasets and selecting subsets of features that are the most predictive of disorders. The Analysis of academic journals and the development of solutions based on the contents of these publications. The use of scoring metrics to determine the suitability models.

Teaching methods

Teaching method Contact Online
Lectures 20 h 0 h
Independent work 60 h 0 h

Teaching language


Modes of study

Option 1
Available for:
  • Degree Programme Students
  • Other Students
  • Doctoral Students
  • Exchange Students
Participation in classroom work
  • In English
Project / practical work
  • In English
Participation in classroom work and Project / practical work

Active participation in class discussions is required and the completion of a project based on the skills taught in class will need to be completed.


Numeric 0-5.

Study materials

Academic publications to be distributed during lectures.

Belongs to following study modules

Department of Future Technologies
Department of Future Technologies
Department of Future Technologies
Archived Teaching Schedule. Please refer to current Teaching Shedule.
Implementation details are unavailable.
Department of Future Technologies
DP in Computer Science
DP in Electr. and Communication Technology
Finnish Study Modules