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The course introduces the student to the area of bioinformatics focusing on the research of fundamental building and functional units of organisms - DNA, RNA and proteins. The student finds out what types of main respositories of related biological data exist and how to handle these data. The fundamental similarity models will be introduced along with the algorithms build on top of the DNA/RNA/proteins contributing to the research in the fields such as mass spectrometry, protein function discovery, structure prediction used in the drug discovery, etc.
Last update: HOKSZAD (05.07.2013)
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Students will be able to: Have insights into algorithms for sequential and structure bioinformatics Develop their own bioinformatics algorithms Modify existing state-of-the-art bioinformatics algorithms Last update: TAJ143 (25.09.2013)
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R: Zvelebil, M., Baum J.: Understanding Bioinformatics, Garland Science; 1 edition, 2007, 0815340249 R: Durbin, R., et al.: Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids, Cambridge University Press, 1998, 0521629713 A: Mount, D.W.: Bioinformatics: Sequence and Genome Analysis, Second Edition, Cold Spring Harbor Laboratory Press, 2004, 0879696087 A: Gusfield, D.: Algorithms on Strings, Trees and Sequences - Computer Science and Computational Biology, Cambridge University Press, 1997, 0521585198 A: Jones, N.C., Pevzner, P.A.: An Introduction to Bioinformatics Algorithms, The MIT Press, 2004, 0262101068 Last update: TAJ143 (02.07.2013)
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None. Last update: HOKSZAD (05.07.2013)
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Na konci semestru studenti skládají písemnou zkoušku. Last update: ROZ143 (29.04.2011)
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1. Introduction. Existind nuclotide and protein databases. 2. Dynamic programming. 3. DNA and RNA sequence similarity. 4. Protein sequence similarity. 5. DNA motif search. 6. Multiple sequence similarity. 7. Phylogenetic trees. 8. Effective similarity search in DNA, RNA and protein sequence databases. 9. RNA structure similarity algorithms. 10. Mass spectrometry algorithms. 11. Protein structure similarity algorithms I. 12. Protein structure similarity algorithms II. 13. RNA structure prediction. 14. Protein structure prediction. Last update: ROZ143 (29.04.2011)
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none Last update: TAJ143 (02.07.2013)
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Teaching methods | ||||
Activity | Credits | Hours | ||
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi | 1.5 | 42 | ||
Příprava na zkoušku a její absolvování | 0.5 | 14 | ||
2 / 3 | 56 / 84 |
Coursework assessment | |
Form | Significance |
Oral examination | 100 |