ScienceMethod 2023

Methodology of scientific research

Module code


Abbreviated title


Module components

Lecture Medical statistic, tutorial Medical statistics, lecture Systems biology, tutorial Systems biology


Semester 1 (summer semester)

Module coordinator/




S. Freitag-Wolf (IMIS), C. Kaleta (IEM)

Contact hours

Lecture  Med. Statistics 2 CH            Tutorial Med. Statistics 1 CH

Lecture Systems biology 2 CH           Tutorial Systems biology 1 CH




Total: 180 h

Lectures: 120 h
Attendance time 46 h, preparation 30 h, revision 44 h
Tutorials: 60 h
Attendance time 24 h, preparation 16 h, revision 20 h

Credit points

6 (lecture Med. statistics 2 CP, tutorial Med. Statistics 2 CP, lecture Systems biology 1 CP, tutorial Systems biology 1 CP)



Expected outcome

Knowledge: Students

- understand the theoretical and methodological foundations of evidence-based medicine

- know the different designs of medico-scientific research approaches including their respective advantages and disadvantages

- are familiar with common statistical methods

- are familiar with the software R and know basic applications

- are familiar with the ethical principles of Good Clinical Practice

- have a thorough understanding of the concepts of systems biology

- have a sound grasp of bioinformatical workflows used in systems biology
- know the most important data processing techniques for interpretation of large data sets.

Skills: Students

- can apply common statistical methods

- can code simple commands in R and apply them for statistical analysis

- can formulate potential hypotheses based on bioinformatical data analysis results 
- can discuss topics in systems biology adequately with informatics fellow students (terminology and argumentation in discussions subject related and relevant)

- can use their knowledge to work with modeling approaches in future research projects.

Competences: Students

- are able to assess the appropriateness of scientific statements and can evaluate them

- have understood the concept of the computer language R and when and to what aim it is used

- can select a suitable approach to execute a statistical analysis of a given data set, including the use of R.


Lecture Medical statistics: Basics of statistics with regard to their application in medicine: descriptive statistics, probability theory, estimation theory, epidemiology, diagnostic testing, statistical testing, regression and correlation, statistical models.

Tutorial medical statistics: Application and consolidation of knowledge and skills taught in the lecture via exercises using the Software R.

Systems biology lecture and tutorial:

Basic concepts, aims and uses of modeling biological systems; modeling paradigms, modeling metabolic networks, modeling for integration and interpretation of large-scale experimental data sets.

Module evaluation/



Medical statistics:

Written exam (multiple choice)

Systems biology:

Written assignments during semester [compound exam]

Media used

Formula development in class, lecture notes


Medical statistics

Kirkwood BR, Essential Medical Statistics (Wiley-Blackwell, 2nd edition, 2003) [still valid]

Bland M, An Introduction to Medical Statistics (OUP 4th revised edition, 2015)

Pezzullo J, Biostatistics for Dummies (For Dummies, 2013)

Systems biology

Klipp E, Liebermeister W, Wierling C, Kowald A, Systems biology: A Textbook (Wiley 2nd edition, 2016)