Computational Biology I – 23605
(2 hrs/week, 4 CP; Spring 2021)
Erik van Nimwegen
→ This course is part of the BSc Biology and BSc Computational Sciences, and can therefore only be counted to the Wahlbereich. (Of course only for those who have not attended it during their BSc!)
This course provides a general introduction into quantitative analysis of data. Students will be introduced to the modern view of probability theory as a general method for reasoning with incomplete information and, guided by practical examples taken from computational biology, will get acquainted with the most important concepts and methods used in statistical analysis and modelingof data. By the end of the course students should have gained a solid understanding of the fundamentals of probabilistic analysis, and how to apply it to analyze biological data. The course alsoacts to introduce the probabilistic methods which are used in the more sophisticated computational biology applications that are presented in the course Computational Biology II (27247).
Students should fulfil the following prerequisites:
- Mathematics Background: Although no formal requirements are made, the course assumes that students are comfortable with mathematical methods including analysis, calculus, and linear algebra, at a fairly advanced level.
- Computer Science Background: Although not necessarily required, familiarity with the basics of programming is helpful.