Meiosis, linkage mapping, pedigree analysis, genetic epidemiology. DNA and protein sequence analysis, molecular evolution, sequence alignment, database searching. Analysis of microarray expression data.
Mendel and segregation: discussion of his results. Meiosis. Stochastic aspects for recombination. Multilocus mapping in experimental crosses (backcross and F2 intercross); the Lander-Green hidden Markov model for calculating probabilities. Mouse experiments : mapping genes for qualitative and quantitative traits using genome-wide scans. Multilocus mapping in pedigrees: the Lander-Green algorithm again, for modest sized pedigrees. Calculation of probabilities and likelihoods on large pedigrees by the Elston and Stewart algorithm, by Markov chain Monte Carlo, and other approaches. Genetic epidemiology: association and linkage in various settings, including case-control and non-transmitted chromosome controls. Affected sib-pair methods and their extensions. Markov process models for molecular evolution. Sequence alignment: local, global, pairwise and multiple. Database searching: precise and heuristic algorithms. BLAST. Gene families, profiles and HMMs. Computational identification of motifs. Analysis of microarray expression data. Precision, reliability, discriminant and cluster analysis.
Statistics 200A/B or equivalent.
Ott, J. `` Analysis of human genetic linkage'' Rev. ed. Johns Hopkins, 1991.
Durbin, R., Eddy, S., Krogh, A. and Mitchison, G. ``Biological sequence analysis'' Cambridge University Press. 1998.
Waterman, M S ``Introduction to Computational Biology: Maps, sequences and genomes'' Chapman and Hall, London, 1995.
Other references will be given during the course. Notes will be posted.