Cycle E: Computational and Systems Biology
| E1: Current research in Bioinformatics I – 22830 (2 hrs/week, 1 CP; Fall 2024, Lecture series with invited speakers) |
| E2: Current research in Bioinformatics II – 21563 (2 hrs/week, 1 CP; Spring 2025, Lecture series with invited speakers) |
| E3: Programming for Life Science – 43513 (2 hrs/week, 4 CP; Fall 2024, Practical course with exercises to be solved at home) |
| E4: Current Topics in Biophysics – 25661 (3 hrs/week + exercises, 6 CP; Fall 2024, Lecture and exercises) |
| E7: Introduction to R – 48662 (2 hrs/week, 2 CP; Fall 2024, Lecture and exercises) |
| E8: Analysis of Genomics Data with R/Bioconductor – 45038 (2 hrs/week, 2 CP; Spring 2025, Lecture and exercises) |
| E9: Computational Biology II – Sequence Modeling and Analysis – 27247 (2 hrs/week, plus 1h exercises; 4 CP; Spring 2025, Lectures and Exercises) |
| E10: Making of a Drug – 52327 (2 hrs/week, 2 CP; Fall 2024, Lecture series with speakers from industry and academia) |
| Coordinator: Richard Neher |
The seminar series “Current Research in Bioinformatics” and “Making of a Drug” are suited for listeners without a detailed computational background. “Programming for Life Sciences “consists of lectures and exercises, where students are expected to acquire programming skills to be able to solve data analysis problems in life sciences. “Current Topics in Biophysics” make the students familiar with current topics in these sub-fields. Basic programming skills and a solid mathematical background are required. For students interested in computational biology, but without a background in computational sciences, the lecture Computational Biology I is worth attending, but it is not part of the graduate teaching program. Similarly, the block course in Synthetic Systems Biology is recommended to students with basic molecular biology skills and interest in this topic.
Recommended lectures outside the graduate teaching program:
| Synthetic Microbiology – 12469 (3-week block course, 8 CP; Fall 2023) |
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| Computational Biology I: Quantitative Data Analysis – 23605 (2 hrs/week, 4 CP; Spring 2023) |