Syllabus for Modelling in Biology

Modellering i biologi

A revised version of the syllabus is available.


  • 5 credits
  • Course code: 1BG383
  • Education cycle: Second cycle
  • Main field(s) of study and in-depth level: Biology A1N, Computational Science A1N

    Explanation of codes

    The code indicates the education cycle and in-depth level of the course in relation to other courses within the same main field of study according to the requirements for general degrees:

    First cycle

    • G1N: has only upper-secondary level entry requirements
    • G1F: has less than 60 credits in first-cycle course/s as entry requirements
    • G1E: contains specially designed degree project for Higher Education Diploma
    • G2F: has at least 60 credits in first-cycle course/s as entry requirements
    • G2E: has at least 60 credits in first-cycle course/s as entry requirements, contains degree project for Bachelor of Arts/Bachelor of Science
    • GXX: in-depth level of the course cannot be classified

    Second cycle

    • A1N: has only first-cycle course/s as entry requirements
    • A1F: has second-cycle course/s as entry requirements
    • A1E: contains degree project for Master of Arts/Master of Science (60 credits)
    • A2E: contains degree project for Master of Arts/Master of Science (120 credits)
    • AXX: in-depth level of the course cannot be classified

  • Grading system: Fail (U), Pass (3), Pass with credit (4), Pass with distinction (5)
  • Established: 2009-03-12
  • Established by:
  • Revised: 2018-08-30
  • Revised by: The Faculty Board of Science and Technology
  • Applies from: Autumn 2019
  • Entry requirements:

    150 credits including 75 credits in biology, 30 credits in chemistry, and Mathematics and Statistics, 10 credits. Proficiency in English equivalent to the Swedish upper secondary course English 6.

  • Responsible department: Biology Education Centre

Learning outcomes

The aim of the course is to give students with a background in biology basic skills in building and analysing mathematical models of biological systems. On completion of the course, the student should be able to:

  • outline the principles behind modelling - why mathematical models?
  • perform the modelling cycle - (i) translate a biological question into a mathematical model, (ii) analyse the model and (iii) interpret the results
  • choose the appropriate modelling framework for different biological questions - quantitative vs qualitative models - deterministic vs stochastic models
  • analyse models formulated in terms of differential and difference equations: equilibria and their stability, basic numerical methods
  • understand, analyse and apply classic models in ecology and evolution: density-dependent population growth, models of species interactions and structured population models, evolutionary models of allele frequency change and invasion analysis
  • critically interpret scientific papers that are based on mathematical models


  • The modelling cycle: (i) translating a biological question into a mathematical model, (ii) mathematical analysis of the model, and (iii) interpreting the mathematical results in terms of biology
  • Standard models in ecology: models for the dynamics of unstructured and structured populations, models of competition and predation
  • Standard models in evolution: one- and two-locus models, quantitative genetics and the breeders' equation, invasion analysis, the stochastic Wright-Fisher and Moran models for allele frequency change
  • Stability analysis of linear and non-linear models in one and two variables, phase-plane analysis, elementary vector and matrix algebra, eigenvalues and eigenvectors, elementary probability theory.


Lectures, home-assignments and exercise classes.


Home-assignments and active participation during the tutorials.

If there are special reasons for doing so, an examiner may make an exception from the method of assessment indicated and allow a student to be assessed by another method. An example of special reasons might be a certificate regarding special pedagogical support from the disability coordinator of the university.

Reading list

Reading list

Applies from: Autumn 2019

Some titles may be available electronically through the University library.

  • Otto, Sarah P.; Day, Troy A biologist's guide to mathematical modeling in ecology and evolution

    Princeton, N.J.: Princeton University Press, cop. 2007

    Find in the library