Computational Biology B (FFR115)

(7.5 credit units)


See TimeEdit for schedule.

Guest lectures:
DNA sequencing - the past, the present, and the future  (A. Blomberg, University of Gothenburg) Mon Feb. 10 10-12 in EC Salen. Lecture notes: pdf.
Statistical inference  (S. Sagitov, Chalmers) Wed Feb. 12 10-12 in EC Salen. Map. Lecture notes: link.


Molecular Biology aims at explaining the chemical structures and processes determining life. Due to new measurement techniques information on structure and function of biological macromolecules has increased significantly in recent years. The amount of data is so huge that it has become necessary to use computational and statistical methods to analyse the data. Further, new experimental data allow statistically significant testing of models for genetic evolution. This has led to a renewed interest in evolution models on the genetic and molecular level. New numerical algorithms and mathematical models have been developed describing population genetics. It is the aim of this course to introduce the mathematical models and computational methods used in the analysis and modelling of genetical data and their evolution.

1. Introduction to the course (course content, basic concepts)
2. Models of proteins: structure and dynamics
3. Genetic maps: sequencing, the double digest problem
4. Markov-chain Monte-Carlo techniques
5. Evolution of genes: Mendelian inheritance, Wright Fisher dynamics, genetic drift
6. Analysing patterns of genetic variation (mutations (single-nucleotide popymorphisms, microsatellites),
7. Effective population size, the molecular clock
8. Population structure: population expansions, founder events, bottlenecks,
9. Geographic structure
10. Bayesian methods
11. Multi-locus data: the coalescent with recombination
12. Selection          


W. J. Ewens, Mathematical population genetics, Springer (1979)
E. S. Lander and M. S. Waterman, eds., Calculating the secrets of life, National Academic Press, Washington (1995). An on-line version of this book is available.
A. Okubo, Diffusion and ecological problems: mathematical models, Springer (1980)
J. D. Murray, Mathematical Biology, Springer (1989)
M. S. Waterman, Introduction to Bioinformatics, Chapman and Hall (1995); Errata
W. Ewens and G. Grant, Bioinformatics, to be published in May 2001
M. T. Madigan, J. M. Martinko and J. Parker, Biology of microorganisms, Prentice Hall (2000)
N. G. van Kampen, Stochastic processes in physics and chemistry, North-Holland (1981)


The exam consists of compulsory homework problems.