Essential Bioinformatics - B143002
Title: Základy bioinformatiky
Guaranteed by: Department of Informatics and Chemistry (143)
Faculty: Faculty of Chemical Technology
Actual: from 2023
Semester: summer
Points: summer s.:5
E-Credits: summer s.:5
Examination process: summer s.:
Hours per week, examination: summer s.:2/2, C+Ex [HT]
Capacity: unknown / unknown (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Level:  
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Svozil Daniel prof. Mgr. Ph.D.
Interchangeability : N143030, N143030A
Examination dates   
This subject contains the following additional online materials
Annotation -
The course introduces a multidisciplinary field of bioinformatics. Bioinformatics deals with the methods for storing, retrieving and analyzing biological data, such as nucleic acid (DNA/RNA) and protein sequence, structure, function, pathways and genetic interactions. Students will be introduced to the basic concepts of bioinformatics and computational biology. Hands-on sessions will familiarize students with the details and use of common online tools and resources.
Last update: Hladíková Jana (04.01.2018)
Aim of the course -

Students will know:

Basics principles of the sequence similarity and homology.

Sequence alignment and sequence database searching.

Molecular phylogenetic analysis.

Prediction of genes and their structure.

Analysis of DNA microarrays data.

Nucleic acids and proteins structure and its prediction.

Last update: Hladíková Jana (04.01.2018)
Course completion requirements -

A credit: a practical project + a protocol

An exam: a written test

Last update: Svozil Daniel (26.01.2018)
Literature -

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 (21.03.2019)
Requirements to the exam -

A credit: a practical project

An exam: a written test

Last update: Svozil Daniel (17.02.2018)
Syllabus -

1. Genomics, genome mapping and sequencing, human genome project

2. Pairwise sequence alignment - homology and similarity, basic principles of alignment

3. Pairwise sequence alignment - scoring, substitution matrices PAM and BLOSUM, dot plot

4. Searching in sequence databases, BLAST

5. Multiple sequence alignment - scoring and creation

6. Position specific substitution matrices, profiles and Hidden Markov Models, PSI-BLAST

7. Molecular phylogenetic analysis - molecular evolution, phylogenetic trees, models of evolution

8. Molecular phylogenetic analysis - methods of phylogenetic trees construction, evaluationg phylogenetic trees

9. Gene detection in eukaryotes and prokaryotes, prediction of introns and exons

10. DNA microarrays, gene expressionanalysis

11. Structure of biomacromolecules - Protein Databank, protein structure classification - SCOP and CATH

12. Prediction of the secondary protein structure

13. Prediction of the tertiary protein structure - homology modeling, threading, ab initio methods, CASP

14. RNA structure and its prediction

Last update: Hladíková Jana (04.01.2018)
Learning resources -

Lecture (video and slides) "Computational molecular biology" at Stanfordu: http://biochem218.stanford.edu/

Videocourse "DNA/Protein Sequence Analysis" by Amy Denton at iTunes: https://itunes.apple.com/itunes-u/dna-protein-sequence-analysis/id472584215?mt=10

Videocourse "Skiena's Computational Biology Lectures" is focused on how the algorithms work than on how to use them: http://www.algorithm.cs.sunysb.edu/computationalbiology/

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 (21.03.2019)
Registration requirements -

Molecular Biology/Genetics, Biochemistry

Last update: Hladíková Jana (04.01.2018)
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
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