Topics in Computational Biology
This module handbook serves to describe contents, learning outcome, methods and examination type as well as linking to current dates for courses and module examination in the respective sections.
MA5607 is a semester module in English language at Master’s level which is offered irregular.
This Module is included in the following catalogues within the study programs in physics.
- Elective Modules Natural Sciences in the Master Program Matter to Life
|Total workload||Contact hours||Credits (ECTS)|
|180 h||60 h||6 CP|
Content, Learning Outcome and Preconditions
- Statistical inference for dynamical biological systems
- Models of Stem Cell Decision Making
- Quantitative models of transcriptional gene regulation
- Hidden Markov Models for the analysis of epigenomics data
- Polygenic Risk Analysis
- Imputing single-cell gene expression
- understand a selection of methods used in computational biology
- understand advantages and disadvantages of the introduced methods
- can evaluate which methods can be used to approach a given problem.
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
|VO||2||Topics in Computational Biology||Marr, C. Peng, T. Theis, F.||
Wed, 14:00–16:00, MI 02.06.011
|UE||2||Topics in Computational Biology (Exercise Session) [MA5607]||Marr, C. Peng, T. Theis, F.||
Wed, 16:00–18:00, MI 02.06.011
Learning and Teaching Methods
- The weekly lecture includes one introductory lecture and 12 lectures introducing specific research questions and computational approaches, given by group leaders from the ICB (see http://icb.helmholtz-muenchen.de for an overview).
- In parallel, each lecture will be accompanied by an exercise course that gives students hands-on experience of the research topics addressed in the lecture. Participation to the exercise
course is compulsory and should be registered to the exercise group via Moodle and TUMonline. All participants should bring their own laptop for the exercises and should install the latest version of the Jupyter Notebook with Python kernel. The lecturer and teaching assistant are present during each exercise course to give professional advices.
F. Markowetz (2017) All biology is computational biology. PLOS Biology.
Description of exams and course work
The exam may be repeated at the end of the semester.