Mathematical Models in Biology
Module MA3601
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.
Module version of SS 2019
There are historic module descriptions of this module. A module description is valid until replaced by a newer one.
Whether the module’s courses are offered during a specific semester is listed in the section Courses, Learning and Teaching Methods and Literature below.
| available module versions | ||||
|---|---|---|---|---|
| SS 2021 | SS 2020 | SS 2019 | SS 2012 | WS 2011/2 |
Basic Information
MA3601 is a semester module in English language at Master’s level which is offered in winter semester.
This Module is included in the following catalogues within the study programs in physics.
- Catalogue of non-physics elective courses
| Total workload | Contact hours | Credits (ECTS) |
|---|---|---|
| 270 h | 90 h | 9 CP |
Content, Learning Outcome and Preconditions
Content
Introduction in theory and application of dynamical systems and stochastic processes: linear compartmental models, Markov-chains, Galton-Watson processes, birth-death-processes, population models, spatial models and age structured models.
Learning Outcome
This module imparts the ability to formulate mathematical models for biological systems on the basis of analytic, stochastic or discrete mathematical structures. The emphasis of the module is to teach the understanding of the importance for different model approaches for one single biological system. At the end of the module, the student is able to evaluate the connection of different results related to different model approaches (stochastic/deterministic, discrete/continuous) and to choose the appropriate level for the description of the system under observation.
Preconditions
MA1001 Analysis 1, MA1002 Analysis 2, MA1101 Linear Algebra and Discrete Structures 1, MA1102 Linear Algebra and Discrete Structures 2, MA1401 Introduction to Probability Theory
Bachelor 2019: MA0001 Analysis 1, MA0002 Analysis 2, MA0004 Linear Algebra 1, MA0005 Linear Algebra 2 and Discrete Structures, MA0009 Introduction to Probability Theory and Statistics
Bachelor 2019: MA0001 Analysis 1, MA0002 Analysis 2, MA0004 Linear Algebra 1, MA0005 Linear Algebra 2 and Discrete Structures, MA0009 Introduction to Probability Theory and Statistics
Courses, Learning and Teaching Methods and Literature
Courses and Schedule
WS 2022/3
WS 2021/2
WS 2020/1
WS 2019/20
WS 2018/9
WS 2017/8
WS 2016/7
WS 2015/6
WS 2014/5
WS 2013/4
WS 2012/3
WS 2011/2
WS 2010/1
| Type | SWS | Title | Lecturer(s) | Dates | Links |
|---|---|---|---|---|---|
| VO | 4 | Mathematical Models in Biology 1 | Müller, J. |
Wed, 08:30–10:00, MI HS3 Fri, 08:30–10:00, MI HS3 Fri, 14:00–16:00, MI 02.04.011 and singular or moved dates |
eLearning |
| UE | 2 | Exercises for Mathematical Models in Biology 1 | John, S. Müller, J. | dates in groups |
documents |
Learning and Teaching Methods
lecture, exercise course, self study exercises
Media
blackboard
Literature
J.D. Murray, Mathematical Biology. Springer-Verlag, 3rd ed. in 2 vols.:
Mathematical Biology: I. An Introduction, 2002;
Mathematical Biology: II. Spatial Models and Biomedical Applications, 2003;
P. Jagers: Branching Processes With Biological Applications. Wiley, London 1975
Mathematical Biology: I. An Introduction, 2002;
Mathematical Biology: II. Spatial Models and Biomedical Applications, 2003;
P. Jagers: Branching Processes With Biological Applications. Wiley, London 1975
Module Exam
Description of exams and course work
The module examination is based on a written exam (60-90 minutes) or an oral exam (20-30 minutes). Students have to understand basic analytic, stochastic and discrete structures to model biological systems and can evaluate the connection of different results related to different model approaches. They are able to choose the appropriate models.
Exam Repetition
The exam may be repeated at the end of the semester.