The course teaches computational methods and first hands-on applications by starting from biological problems/phenomena that students in the 4th semester are somewhat familiar with. During the exercises, students will obtain first experience with programming their own analyses/models for data analysis/interpretation.
Learning objective
We will teach little if any novel biological knowledge or analysis methods, but focus on training the ability of use existing knowledge (for example from enzyme kinetics, regulatory mechanisms or bioanalytical and statistical methods) to understand biological problems that arise when considering molecular elements in their context and to translate some of these problems into a form that can be solved by computational methods. Specific goals are: - understand the limitations of intuitive reasoning - obtain a first overview of computational approaches in systems biology - train ability to translate biological problems into computational problems - solve practical problems by programming with MATLAB - make first experiences in computational interpretation of biological data - understand typical abstractions in modeling molecular systems
Generally, we train critical thinking and active use of knoweldge in application to conrete biological problems.
Content
During the first 7 weeks, the will focus on mechanistic modeling. Starting from simple enzyme kinetics, we will move through the dynamics of small pathways that also include regulation and end with flux balance analysis of a medium size metabolic network. During the second 7 weeks, the focus will shift to the analysis of larger data sets, such as proteomics and transcriptomics that are often generated in biology. Here we will go through multivariate statistical methods that include clustering and principal component analysis, ending with first methods to learn networks from data.
Lecture notes
Scripts to prepare the lectures will be provided via Moodle
Competencies
Subject-specific Competencies
Concepts and Theories
assessed
Techniques and Technologies
assessed
Method-specific Competencies
Analytical Competencies
assessed
Problem-solving
assessed
Personal Competencies
Creative Thinking
assessed
Critical Thinking
assessed
Performance assessment
Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
In examination block for
Bachelor's Degree Programme in Biochemistry - Chemical Biology 2020; Version 28.11.2022 (Examination Block I)
The performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examination
written 120 minutes
Additional information on mode of examination
Die Vorlesung wird durch Übungen auf einer Lernplattform (Moodle) und Gruppenübungen begleitet. Bei erfolgreicher Teilnahme an den Übungen (mindestens 75% der Aktivitäten müssen erfolgreich abgeschlossen sein) können die Studierenden einen Bonus von 0.25 Notenpunkten erhalten, der auf die Schlussnote der Prüfung angerechnet werden kann. Die Maximalnote 6 für die Lerneinheit kann auch erreicht werden, wenn nur die Sessionsprüfung absolviert wird.
Written aids
None
Distance examination
It is not possible to take a distance examination.
If the course unit is part of an examination block, the credits are allocated for the successful completion of the whole block. This information can be updated until the beginning of the semester; information on the examination timetable is binding.
Learning materials
No public learning materials available.
Only public learning materials are listed.
Groups
No information on groups available.
Restrictions
There are no additional restrictions for the registration.
Performance assessment as a semester course