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Computational science: Systems Biology – Models and Computations (BERN06), 7.5 credits

In systems biology, biological phenomena are studied from the perspective that complexity arises from the interactions of simpler components such as molecules, cells or individuals. In this course you will learn how different biological systems can be translated into equations and simulated in different ways on computers.

The systems biology perspective can be applied at many different scales and levels of detail, from a few molecules to billions of living cells. Networks of interacting molecules, genes, proteins, cells or individuals are treated the same way, with equations reflecting the properties and interactions of the different building blocks. Different kinds of models may be used to describe and understand how systems work, but typical of systems biology is a repeated cycle of modelling, simulation, experimentation and comparison.

In this course you will formulate equations for different systems and express them as computer code. You will perform simulations, study how the systems behave and make comparisons with data. The course delves into how and when biological systems can be simulated deterministically and stochastically, as well as how to treatment systems with spatial dimensions and transport mechanisms.

Programming is an important part of the course, and you may choose to work in Python or other languages. 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. Among other things, we go through the Gillespie algorithm for stochastic simulations and various methods for optimising model parameters.

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 as well as different ways of visualising the results.

Who can take the course?

The course is designed for students with knowledge in computational physics or modelling from at least a couple of years of bachelor studies. The formal requirements are 90 credits in natural science including knowledge equivalent to BERN01 Modeling in Computational Science or FYTN03 Computational Physics.

The course is given at half speed during the second half of the spring term. We try to avoid scheduling clashes with other courses that students have applied to. Doctoral students are also welcome to take the course (course code NTF015F) and are asked to contact the course coordinator well before the course starts. The course has previously been given under the course code FYTN12.

More information about the course content, schedule and course evaluations can be found on the permanent course page on Canvas:

Eligibility & selection, application and admission

On the Lund University central website you will (eventually, closer to the application date) find syllabus, eligibility & selection, application & admission information.

Systems Biology – Models and Computations (BERN06)

Course code: BERN06
Credits: 7,5 hp
Cycle: Second cycle
Period: Spring term, period 2, half speed


Schedule for BERN06 spring 2024 on TimeEdit –

Course literature

Slides and lecture notes on the course website.

Course analyses

See the course page on Canvas

Course coordinator

Victor Olariu
Email: victor [dot] olariu [at] cec [dot] lu [dot] se (victor[dot]olariu[at]cec[dot]lu[dot]se)