Computational Biology

Basic programming and use of computer packages. Data types, control flow, functions, graphical techniques. Methods for simulation of random variables, solution of non-linear equations, numerical maximum likelihood computation, methods for non-parametric and parametric bootstrapping. Simulation of deterministic, stochastic and chaotic dynamic model. Age structure, genetic drift, environmental and demographic variance.

The course aims at giving the students a basic introduction to programming techniques useful in statistical and stochastic modelling in biology.

Lectures, compulsory exercises and mid-semester examination.
Portfolio assessment is the basis for the grade awarded in the course. This portfolio comprises a written final examination 60%, compulsory exercises (20%) and the semester assignment 20%. The mid-semester examination only counts if it has a positive effect on the total assessment. The results for the constituent parts are to be given in %-points, while the grade for the whole portfolio (course grade) is given by the letter grading system.

Retake of examination may be given as an oral examination.