PřF:C2131 Introduction to bioinformatics - Course Information
C2131 Introduction to bioinformatics
Faculty of ScienceSpring 2021
- Extent and Intensity
- 2/0/0. 2 credit(s) (plus 2 credits for an exam). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Michaela Wimmerová, Ph.D. (lecturer)
Mgr. Lenka Malinovská, Ph.D. (lecturer)
Mgr. Josef Houser, Ph.D. (lecturer) - Guaranteed by
- prof. RNDr. Michaela Wimmerová, Ph.D.
National Centre for Biomolecular Research – Faculty of Science
Supplier department: National Centre for Biomolecular Research – Faculty of Science - Timetable
- Mon 1. 3. to Fri 14. 5. Thu 10:00–11:50 online_BCH4, Thu 10:00–11:50 online_BCH4
- Prerequisites
- Basic knowledge of biomacromolecules (proteins, nucleic acids).
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Bioinformatics (programme PřF, B-BIC)
- Epidemiology and modeling (programme PřF, B-MBB)
- Course objectives
- The goal of this course is acquiring of basic knowledge of bioinformatics and its potential practical usage. The course will be focused on nucleic acids (including RNA) and proteins. However, other biomolecules as carbohydrates and lipids (which are usually neglected) will be discussed as well. The course will also deal with posttranslational modifications and their predictions that could be crucial for physiological functions of proteins. Students will also acquire basic knowledge of small molecules which are frequently important interaction partners of biomacromolecules. Also, the processing of large quantity of bioinformational data will be discussed. The course will also introduce specific bioinformational tools and programs which will be used and taught in the concurrent seminar.
- Learning outcomes
- At the end of the course students should: 1) Obtain basic knowledge of bioinformatics. Students should be able to: 1) Process bioinformational data. 2) Predict basic properties of biomacromolecules. 3) Utilize bioinformational tools for solving of biological problems.
- Syllabus
- 1) Introduction. Organizational information. Recommended literature. History of bioinformatics. Basics of information search. Bioinformatical data. 2) Nucleic acids. Composition, structure and function of nucleic acids. Base pairing, double helix. Genetic information, gene, genetic code. Reading frames. Nucleic acid sequences, nucleic acid databases. 3) Proteins. Composition, structure and function of proteins. Proteogenic amino acids. Non-standard amino acids in proteins. Amino acid nomenclature, abbreviations. Translation. Protein sequences, protein databases. Protein structure determination, structural databases. 4) Alignment. Molecular phylogeny. Phylogeny data. Trees and methods of their building-up. 5) Gene and promotor prediction. Prokaryotes. Eukaryotes. Prediction based on sequence homology, ab initio prediction. Tools and programs for gene prediction. 6) Tools for nucleic acid analysis. Palindromes. Restrictases. Restrictase on-line databases. PCR. Primer design. 7) RNA properties and tools for their prediction. RNA structure prediction. RNA bioinformatics. 8) Prediction of protein properties. Prediction of protein basic properties and localization. Prediction of posttranslational modifications. Prediction of interacting partners. 9) 2D, 3D and 4D protein structure prediction. Coordinates. Formats. Visualization tools. 10) Saccharides and lipids. Structure, importance and function. Bioinformatical potential of saccharides. Glycoproteins and their encoding in genome. Nomenclature and graphical representation. Databases and tools for glyco- and lipido- bioinformatics. 11) Small molecules. Importance, function, databases. 12) Experimental methods. Their relation to bioinformatics, overlap between bioinformatics and laboratory praxis.
- Literature
- recommended literature
- SELZER, Paul M., Richard J. MARHÖFER and Andreas ROHWER. Applied bioinformatics : an introduction. 1st pub. in Germen under the. Berlin: Springer, 2008, xiv, 287. ISBN 9783540727996. info
- XIONG, Jin. Essential bioinformatics. 1st pub. Cambridge: Cambridge University Press, 2006, xi, 339. ISBN 0521600820. info
- Teaching methods
- Lectures, presentations by invited professionals, class exercises.
- Assessment methods
- Oral exam.
- Language of instruction
- Czech
- Further Comments
- Study Materials
- Enrolment Statistics (Spring 2021, recent)
- Permalink: https://is.muni.cz/course/sci/spring2021/C2131