Tik-61.181 Timetable

The first topics will be assigned on 19.9., and the rest on 26.9.

There is a relatively lot material under each topic so the idea is not to present all algorithmic details and variations. The details will be considered in the exercises.

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.
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.
SSK, Ch.4 + DEKM, Ch.3, myös BB, Ch.7-8: An introduction to hidden Markov models for biological sequences (1 presentation: an overview of the methods + exercise) (20p.+34p.+58p.)
    DEKM, Ch.4: Pairwise alignment using HMMs (20p.)
DEKM, Ch.5: Profile HMMs for sequence families (34p.)
    DEKM, Ch.6: Multiple sequence alignment methods (26p)
SM, Ch.4: Fragment assembly of DNA (38p.)
    SM, Ch.5: Physical mapping of DNA (32p.)
SM, Ch.6: Phylogenetic trees (also DEKM: Ch.7) (40p.+32p.)
    DEKM, Ch.8: Probabilistic approaches to phylogeny, myös BB, Ch.10 (41p.+12p.) ("comparison of probabilistic and non-probabilistic methods": exercise)
SM, Ch.7: Genome rearrangements (30p.)
    SM, Ch.8: Molecular structure prediction (16p.)
DEKM, Ch.9: (Stochastic) transformational grammars, myös BB, Ch.11 (27p.+22p.)
    DEKM, Ch.10: (Probabilistic) RNA structure analysis (39p.)
SSK, Ch.11: Statistical analysis of protein structures (20p.)
    SSK, Ch.12: Analysis and algorithms for protein sequence-structure alignment (For 2 people together!) (58p.)
SSK, Ch.13: THREADER: protein sequence threading by double dynamic programming (28p.)
    SSK, Ch.14: From computer vision to protein structure and association (22p.)
    SSK, Ch.15: Modeling biological data and structure with probabilistic networks (20p)
SSK, Ch.5: Case-based reasoning driven gene annotation (22p.)
    SSK, Ch.7: Computational gene prediction using neural networks and similarity search (20p.)
    SSK, Ch.10: Decision trees and Markov chains for gene finding (20p.)
5.12. (time may change!) Invited speakers
Symposium on bioinformatics

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Friday, 22-Sep-2000 08:36:09 EEST