Bioinformatics
General description
Course organized by TUT, see TUT study guide for up-to-date information.
Learning outcomes
After completing the course, the student can:
- gained a basic understanding of the definition and the meaning of computational diagnostics and its utility for biomedical research.
- Case studies will be discussed illustrating the interplay between computational and statistical methods that are applied to large-scale and high-dimensional data sets from genomic and genetic experiments.
- Moreover, the student will learn how to practically approach such problems by using the statistical programming language R.
- In general, the course teaches statistical thinking in the context of biomedical problems, i.e., the adaptation of machine learning methods in a problem specific manner.
Contents
- Classification of disease groups
- Biomarker identification
- Survival analysis
- Human disease network
Modes of study
- Degree Programme Students
- Other Students
- Open University Students
- Doctoral Students
- Exchange Students
Evaluation
Numeric 1-5.Belongs to following study modules
2018–2019
