Computational Biology B (FFR 115)

Graphs and Genes, Genetic Drift and Diffusion

(7.5 credit units)

Teachers:

Bernhard Mehlig
Marina Rafajlovic

Examiner:

Bernhard Mehlig

Schedule

First lecture Monday January 16, 15-17 in MC Salen
For the teaching schedule please check TimeEdit.

Course evaluation

N.N
N.N

Link to course evaluation

Examination

Translation table GU grades to ECTS grades.

Abstract

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.

Plan

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

Literature

1. W. J. Ewens, Mathematical population genetics, Springer (1979)
2. 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.
3. A. Okubo, Diffusion and ecological problems: mathematical models, Springer (1980)
4. J. D. Murray, Mathematical Biology, Springer (1989)
5. M. S. Waterman, Introduction to Bioinformatics, Chapman and Hall (1995); Errata
6. W. Ewens and G. Grant, Bioinformatics, to be published in May 2001
7. M. T. Madigan, J. M. Martinko and J. Parker, Biology of microorganisms, Prentice Hall (2000)
8. N. G. van Kampen, Stochastic processes in physics and chemistry, North-Holland (1981)

All books are available at the Chalmers library (or the medical library), and also at my office. You are encouraged to come to my office and consult the literature. A number of research papers will also be referred to and will be made available:

1. R. R. Hudson, Gene genealogies and the coalescent process, in: Oxford surveys in evolutionary biology, eds: D. Futuyama and J. Antonovics, Oxford University Press, Oxford (1990)
2. T. Murayama and M. Kimura, Genetic variability and effective population size when local extinction and recolonizatn of subpopulations are frequent, Genetics 77, 6710 (1980)
3. C. Wiuf and Jotun Hein, The coalescent with gene conversion, Genetics 155 (2000) 451
4. J. Maynard Smith, Estimating the minimum rate of genetic transformation in bacteria, J. evol. Biol. 7 (1994) 525
5. R. R. Hudson, Analytical results concerning linkage disequilibrium in models with genetic transformation and conjugation, J. evol. Biol. 7 (1994) 535
6. J. F. C. Kingman, The coalescent, Stochastic Processes and their Applications 13 (1982) 235

More references are given at the end of each chapter.

Lecture notes

Lecture notes will be provided.

Examples

Link to page with examples sheets and instructions.

Further Resources