BERN06: Systems Biology – Models and Computations, 7.5 credits

This is an advanced level course in computational science, course code BERN06, given by the Centre for Environmental and Climate Science (CEC). The course was previously given by the Department of Astronomy and Theoretical Physics with the course code FYTN12.

Note: this page contains general information about the course. If you are a student on the course you have to log in to the canvas portal to the left to see the 2025 course instance. The course calendar and course stream on this page are not active.

Background

Systems biology is a broad scientific field where biological phenomena are studied from the perspective that complex properties arise from the interaction of individual parts. This perspective can be applied at many different scales and levels of detail, from a few molecules to billions of living cells or individuals. Different types of models can be used to describe and understand how a system works, but typical of systems biology is a repeated cycle of modelling, simulation, experimentation and comparison.

Course contents

In this course you will learn how biological systems can be translated into equations that can then be simulated numerically in different ways. Networks of interacting molecules, genes, proteins, cells or individuals are treated similarly, with equations reflecting the properties and interactions of the different building blocks. You will learn to formulate equations for different systems and translate them into computer code to perform simulations, study how the systems behave and compare with measured data.

Programming is an important part of the course, and you can choose to work in Python or some other language. The course covers how and when biological systems can be simulated deterministically and stochastically. You are expected to be familiar with numerical integration of ordinary differential equations but may use existing packages for e.g. the Runge-Kutta method. You will learn the Gillespie algorithm for stochastic simulations, as well as how to handle systems with spatial dimensions and transport mechanisms. Detailed course goals can be found in the syllabus (see below).

The course is divided into five parts, where each part consists of lectures and an individual programming project which you present orally. The projects give ample room for your own ideas and investigations and different ways of visualising the results.

General information

Period: Spring term, study period 2, half speed
Cycle: Second/third cycle
Language: English
Forms of teaching: Lectures, programming projects
Assessment: Project presentations, oral exams
Grading scale: U-G-VG
Syllabus: BERN06 syllabus in English and in Swedish
PhD course: NTF015F syllabus in English and in Swedish

Course literature

The lectures are based on our slides and lecture notes as well as on papers from the scientific literature.
Suggested extra reading (largely outside the scope of the course):
- An Introduction to Systems Biology: Design Principles of Biological Circuits, second edition, Uri Alon. Taylor & Francis (2019).
- Physical Biology of the Cell, second edition Rob Phillips, Jane Kondev, Julie Theriot, Hernan G. Garcia. Garland Science (2012).

Teachers

The teachers are located at Computational Science for Health and Environment (COSHE, formerly CBBP), CEC, with offices on floor 5 of the Geocentrum II building.

Victor Olariu (Course coordinator, email: victor.olariu@cec.lu.se, phone: 046-222 3496)
Carl Troein, carl.troein@cec.lu.se
Henrik Jönsson, henrik.jonsson@slcu.cam.ac.uk

Schedule

The schedule for the spring term 2025 is available in TimeEdit.

Course evaluations

Spring 2015: Course evaluation
Spring 2016: Course evaluation, Response
Spring 2017: Course evaluation, Response
Fall 2018: Course evaluation, Course analysis
Fall 2020: Course evaluation, Course analysis
Fall 2022: Course analysis

Application

Apply through antagning.se. The course will be open for late applications.

PhD students are welcome to join the course. It is advisable to contact us in advance to get added on Canvas.