Tik-61.181 Timetable

There is quite a lot of material under each topic. The idea is to concentrate on the most important matters and not to present all algorithmic details and variations. (Note, however, that some algorithmic details are important!)

The length of the presentations should be 20 min. (Maximally a total of 30 min, including the discussion.) Note that the time limit is strict when there are three presentations within 90 min!

References to books:
SM: Setubal & Meidanis
SSK: Salzberg, Searls, Kasif
DEKM: Durbin, Eddy, Krogh, Mitchison
BB: Baldi & Brunak - this is only complementary material

Date	Speaker	Topic
19.9.	Heikki Mannila, Sami Kaski	Opening lecture, general information.
26.9.		The topics and the rest of the timetable will be fixed. Homework: read Ch. 1-2 of Setubal & Meidanis (S&M)
	Teemu Karevaara	Sequence comparison. S&M: Ch. 3.1-3.4.
	Ville Viitaniemi	Database search + other issues. S&M: Ch. 3.5-3.6.
3.10.	Raul Lozano	SSK, Ch.4 (20p.)+ DEKM, Ch.3 (34p.), (supplementary material BB, Ch.7-8 (58p.)): An introduction to hidden Markov models for biological sequences (an overview of the methods)
	Jouni Seppänen	DEKM, Ch.4: Pairwise alignment using HMMs (20p.)
10.10.	Anne Patrikainen	DEKM, Ch.5: Profile HMMs for sequence families (34p.)
	Juha Alaluusua	DEKM, Ch.6: Multiple sequence alignment methods (26p)
17.10.	Eero Vaarnas	SM, Ch.4: Fragment assembly of DNA (38p.)
	Jukka Laurila	SM, Ch.5: Physical mapping of DNA (32p.)
24.10.	Janne Sinkkonen	SM, Ch.6: Phylogenetic trees (40p.),(supplementary material DEKM: Ch.7 (32p.))
	Jarkko Salojärvi	DEKM, Ch.8: Probabilistic approaches to phylogeny (41p.), (supplementary material BB, Ch.10 (12p.))
31.10.	Olli-Pekka Rinta-Koski	SM, Ch.7: Genome rearrangements (30p.)
	Markku Roiha	SM, Ch.8: Molecular structure prediction (16p.)
7.11.	Antonio Villena	DEKM, Ch.9: (Stochastic) transformational grammars (27p.), (supplementary material BB, Ch.11 (22p.)
	Ismo Haanaho	DEKM, Ch.10: (Probabilistic) RNA structure analysis (39p.)
14.11.	Jarkko Venna	SSK, Ch.11: Statistical analysis of protein structures (20p.)
	Jörkki Hyvönen	SSK, Ch.12: Analysis and algorithms for protein sequence-structure alignment (For a group of 2 people) (58p.)
21.11. (NOTE! Read the introduction papers to micro array methods before this day!)	Satu Nahkuri	Microarrays and gene regulatory networks Chen et al.: Identifying gene regulatory networks from experimental data, ACM RECOMB 1999, pp.94-103 Brazma et al.: Predicting gene regulatory elements in silico on a genomic scale, Brazma et al., Genome, vol 8, pp.1202-1215, 1998))
	Mika Inki	SSK, Ch.14: From computer vision to protein structure and association (22p.)
	Vesa Siivola	SSK, Ch.15: Modeling biological data and structure with probabilistic networks (20p)
28.11. (time has changed!)	Invited speakers	Symposium on bioinformatics
5.12.	Petri Loukasmäki	Microarrays and gene expression clustering Ben-Dor:Clustering gene expression patterns , ACM recomb 1999, pp.33-42 Tamayo et al.: Interpreting patterns of gene exspression with self-organizing maps: Methods and application to hetopoietic differentiation, Proc.Natl.Acad.Sci.USA, vol96,pp.2907-2912,1999 Eisen et al.: Cluster analysis and display of genome-wide expression patterns PNAS USA, vol95, pp. 14863-14868,1998)
	Matti Aksela	SSK, Ch.7: Computational gene prediction using neural networks and similarity search (20p.)
	Harri Laakso	SSK, Ch.10: Decision trees and Markov chains for gene finding (20p.)
12.12.	Julian Cobos	Microarrays and gene expression analysis and classification Brown et al.: Knowledge-based analysis of microarray gene expression data by using support vector machines, PNAS 2000, vol 97.,pp.262-267 Alter et al.: Singular Value decomposition for genome-wide expression data processing and modeling, PNAS 2000, vol.97,pp.10101-10106
	Ville Könönen	SSK, Ch.13: THREADER: protein sequence threading by double dynamic programming (28p.)

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