Required in stage
First term
Second term
Both terms
This year
Next year
Alternating years
External
Prerequisites
Language of instruction
Duration
LevelTheoretical Modelling in Biology (B-KUL-G0G41A)
Wenseleers Tom (coordinator) |
Vanoverbeke Joost |
Wenseleers Tom
Aims
The students will acquire expertise in the development of theoretical models in biological research, with emphasis on applications in ecology and evolutionary biology. The students will develop sufficient expertise to make sound decisions with respect to the modeling approach to be taken. Students will be thought how to use modelling tools such as Mathematica, so that they can develop and implement their own theoretical models. Expertise will be obtained in both numerical and analytical techniques. Through relatively simple examples, the students will acquire a feeling for the possibilities and limitations of different modeling approaches.
Previous knowledge
The students have a basic knowledge in ecology and evolutionary biology.
Course material
Text book
Articles and literature
Syllabus
Slides, transparencies, courseware
Examples and samples
Toledo / e-platform
Is also included in other courses
- Master in de biologie (Professional Option) 120 ects.
-
Master of Biology
120 ects.
Activities
1.7 ects. Theoretical Modelling in Biology (B-KUL-G0G41a)
Content
Basic concepts
- Modelling approaches in theoretical biology: analytical models, numerical techniques, simulation
- Different kinds of analytical and numerical models: static vs. dynamic, continuous vs. discrete, optimisation vs. explicit genetic models, individual- and agent-based models
I. Case studies analytical models
- Setting up the basic question: examples from life history evolution (optimal clutch size), behavioural ecology (ESS concept) and population ecology (coexistence of two species)
- Difference and differential equation models; applications from population ecology (population growth, competitive interactions between two species)
- Game theory and inclusive fitness: evolutionarily stable strategies; applications in the areas of social evolution on the evolution of mating strategies
- Explicit genetic models; applications from evolutionary genetics and behavioural ecology
II. Case studies numerical techniques
- Individual- and agent-based models: applications from population-ecology and on self-organising behaviour
III. Beschrijvende ecologische modellen
- Populationdynamic models with interactions between more than two species
- Modelling of food webs
- Spatially explicit models
Exercises
Working out examples using Mathematica
1.3 ects. Theoretical Modelling in Biology: Exercises (B-KUL-G0G42a)
Content
Basic concepts
- Modelling approaches in theoretical biology: analytical models, numerical techniques, simulation
- Different kinds of analytical and numerical models: static vs. dynamic, continuous vs. discrete, optimisation vs. explicit genetic models, individual- and agent-based models
I. Case studies analytical models
- Setting up the basic question: examples from life history evolution (optimal clutch size), behavioural ecology (ESS concept) and population ecology (coexistence of two species)
- Difference and differential equation models; applications from population ecology (population growth, competitive interactions between two species)
- Game theory and inclusive fitness: evolutionarily stable strategies; applications in the areas of social evolution on the evolution of mating strategies
- Explicit genetic models; applications from evolutionary genetics and behavioural ecology
II. Case studies numerical techniques
- Individual- and agent-based models: applications from population-ecology and on self-organising behaviour
III. Beschrijvende ecologische modellen
- Populationdynamic models with interactions between more than two species
- Modelling of food webs
- Spatially explicit models
Exercises
Working out examples using Mathematica
Evaluation
Evaluation : Theoretical Modelling in Biology (B-KUL-G2G41a)
Explanation
Evaluation type: report and presentation
Explanation: Evaluation is based on an individual theoretical modelling project, whereby a model from the literature is validated using Mathematica or Simile and further extended by incorporating one or more additional parameters.
