The course provides an overview of mathematical and computational modelling and analysis methods commonly employed in the studies of complex systems, with special focus on biological and chemical applications.
By the end of the course, the students should be able to independently judge which modelling and analysis techniques are suitable for a given problem definition.
The following topics are covered in the course:
Different model types and their advantages (deterministic vs non-deterministic models, discrete vs continuous models, qualitative vs quantitative models, generative vs agent-based models), Petri nets, Boolean networks, Markov chains and stochastic Petri nets, Kappa (site graph transformation), stochastic simulation, model checking, Petri net unfolding (causal analysis/concurrency), abstract interpretation;
No strict requirements, but at least foundational knowledge of formal methods in software verification, or of graph theory and algorithms, mathematical logic, formal languages, grammars and automata is encouraged.
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Module | Course | Requirements | |
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39-Inf-AB Algorithmen der Bioinformatik | Ausgewählte Vorlesung zu Algorithmen der Bioinformatik | Ungraded examination
Graded examination |
Student information |
39-Inf-SAB_a Spezielle Algorithmen der Bioinformatik | Ausgewählte Vorlesung zu Spezielle Algorithmen der Bioinformatik | Ungraded examination
Graded examination |
Student information |
39-Inf-WP-AP Algorithmen & Programmierung (Basis) | Einführende Vorlesung | Student information | |
- | Graded examination | Student information | |
39-Inf-WP-CLS Computational Life Sciences (Basis) | Einführende Vorlesung | Student information | |
- | Graded examination | Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.