Admission requirements
Calculus (and an interest in biology/biophysics/biochemistry)
Description
The course covers the mathematical modelling, analysis and simulation of various biochemical processes that relate cell signaling, in particular to electrical activity in e.g. neurons and pancreatic beta cells. Modelling and analysis techniques are highlighted by using examples. It is illustrated how models of subsystems (and understanding of their behaviour individually) may be combined to get ‘whole cell’ models and gain insight in their behaviour. Mathematical concepts from dynamical system theory (e.g. equilibria, periodic solutions, bifurcations, time scale analysis, singular perturbation) are introduced in order to analyse and simulate the models using dedicated software. The results are compared to experimental results. At the end of the course the student is acquainted with the fundamental Hodgkin-Huxley, FitzHugh-Nagumo and Morris-Lecar models for electrical activity of cells and the relationships among them and should be capable of exploring further the current research on (biological) neural networks.
Course objectives
The course aims to introduce the student into the broad field of Mathematical Biology. In particular it shows what insights can be gained from the mathematical modelling, and subsequent analysis and simulation of these, into the functioning of complex cellular biological processes. As running example throughout the course functions the topic of electrical signalling of cells. At the end of the course the student is able to construct and comprehend mathematical models of these processes themselves, conduct simulations and interpret the results. Moreover, he/she will be able to read, understand in depth research papers on electrical signalling processes that involve mathematical modelling.
Timetable
The most recent timetable can be found at the LIACS website
Mode of instruction
Lectures
Assessment method
Individual assignments and small-team projects with written report and presentation.
Examination:
The final grade for the course is determined by weighted average of: (1) three take-home assignments (45%) , (2) an individually written essay on a research question covered by a collection (1 – 3) of recent research papers that apply the techniques discussed in the course (35%), which is also worked on in an interdisciplinary team, and (3) a team presentation on the topic of the essay (20%).
Literature
‘Computational Cell Biology’, C.P. Fall, E.S. Marland, J.M. Wagner and J.J. Tyson (eds.), Interdisciplinary Applied Mathematics, Vol. 20, Springer-Verlag, 2002 (ISBN 0-387-95369-9)
Registration
You have to sign up for classes and examinations (including resits) in uSis. Check this link for more information and activity codes.
Contact information
Study coordinator Computer Science, Riet Derogee