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This lecture introduces students to the fundamentals of bioinformatics, a multidisciplinary field that combines computer science, statistics, and biology. Bioinformatics focuses on the storage, organization, retrieval, and, in particular, the analysis and interpretation of large biological datasets. These data include, for example, nucleic acid and protein sequences, their structure, function, and interactions. Students will become familiar with the basic concepts of bioinformatics and tools of computational biology. During the practical sessions, the use and details of commonly used online tools and resources will be demonstrated.
Last update: Svozil Daniel (06.02.2026)
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A credit: a practical project + a protocol An exam: a written test Last update: Svozil Daniel (03.04.2025)
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R:A. Lesk, Introduction to Bioinformatics, Oxford University Press 2014, ISBN 9780199651566 A:P. M. Selzer a kol., Applied Bioinformatics: An Introduction, Springer 2018, ISBN 3319682997 A:J. Pevsner, Bioinformatics and Functional Genomics, Wiley 2017, ISBN 9788126567683 Last update: Svozil Daniel (03.04.2025)
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Credit: practical project Exam: a credit is required to register for the exam; the exam is in the form of a written test Last update: Svozil Daniel (06.02.2026)
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1. Cell biology summary Soubor 2. DNA recombinant technology, genome maps, Sanger sequencing Soubor 3. Genome mapping and sequencing, human genome project 4. Pairwise sequence alignment - homology and similarity, basic principles of alignment 5. Pairwise sequence alignment - scoring, substitution matrices PAM and BLOSUM, dot plot 6. Searching in sequence databases, BLAST 7. Multiple sequence alignment - scoring and creation 8. Molecular phylogenetic analysis - molecular evolution, phylogenetic trees, models of evolution, methods of phylogenetic trees construction 9. Structure of biomacromolecules - Protein Databank, protein structure classification - SCOP and CATH 10. Prediction of the secondary protein structure 11. Prediction of the tertiary protein structure - homology modeling, threading, ab initio methods, CASP 12. RNA structure and its prediction Last update: Svozil Daniel (06.02.2026)
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Lecture (video and slides) "Computational molecular biology" at Stanfordu: http://biochem218.stanford.edu/ Videocourse from Steve Skiena "Introduction to Computational Biology" is focused more on how bioinformatics algorithms work than on how to use them.: https://www3.cs.stonybrook.edu/~skiena/549/ Book "Applied Statistics for Bioinformatics using R" by Wim P. Krijnen - http://cran.r-project.org/doc/contrib/Krijnen-IntroBioInfStatistics.pdf Last update: Svozil Daniel (06.02.2026)
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Students will know: Basics principles of the sequence similarity and homology. Sequence alignment and sequence database searching. Molecular phylogenetic analysis. Nucleic acids and proteins structure and its prediction. Last update: Svozil Daniel (06.02.2026)
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Molecular Biology/Genetics, Biochemistry Last update: Svozil Daniel (03.04.2025)
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| Teaching methods | ||||
| Activity | Credits | Hours | ||
| Účast na přednáškách | 1 | 28 | ||
| Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi | 1 | 28 | ||
| Práce na individuálním projektu | 1 | 28 | ||
| Příprava na zkoušku a její absolvování | 1 | 28 | ||
| Účast na seminářích | 1 | 28 | ||
| 5 / 5 | 140 / 140 | |||

