| Course title | Fundamentals of Bioinformatics |
|---|---|
| Course code | KBC/ZBINF |
| Organizational form of instruction | Lecture + Seminar |
| Level of course | Bachelor |
| Year of study | 1 |
| Semester | Summer |
| Number of ECTS credits | 5 |
| Language of instruction | Czech, English |
| Status of course | Compulsory, Compulsory-optional |
| Form of instruction | Face-to-face |
| Work placements | This is not an internship |
| Recommended optional programme components | None |
| Lecturer(s) |
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| Course content |
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1) Definition of bioinformatics; historical and scientific background of the development of the discipline; goals and methodologies of bioinformatics; nucleotide and amino acid sequences; the genetic code; chemical properties of amino acids and nucleotides; methods for sequence analysis of DNA and proteins. 2) Sequence file formats; advantages of the FASTA format over flat-file and plain text formats; publicly available sequence databases; types of databases (primary vs. secondary); the DDBJ/EMBL/GenBank consortium; accession numbers and taxonomic identifiers; genomic and proteomic databases; bioinformatics resources on the Internet. 3) Extracting information from sequences; sequence motif databases; cellular transport of proteins; prediction of protein subcellular localization; post-translational modifications and their prediction; prediction of protein secondary structures; Gene Ontology (GO) - significance and applications; Gene Ontology browsers; the STRING database (protein-protein interactions). 4) Assessment of sequence similarity; the concept of sequence homology; pairwise and multiple sequence alignment; dot plots; alignment algorithms; substitution matrices; multiple sequence alignment formats; software tools for sequence alignment; the concept of sequence logos (WebLogo). 5) Database searching based on similarity to a known sequence; FASTA and BLAST algorithms; BLAST variants for amino acid and nucleotide sequences; PSI-BLAST and MS-BLAST; searching structural databases using a sequence query - threading (fold-recognition) algorithms. 6) Definition of phylogeny and identification of phylogenetic relationships using bioinformatics tools; distance-based and character-based methods for phylogenetic tree construction - overview, advantages, and disadvantages; assessment of tree reliability using bootstrapping; freely available tools for phylogenetic tree construction; visualization methods - rectangular and radial (star-like) tree layouts. 7) Prokaryotic and eukaryotic genes; gene prediction methods; GENESCAN and NetGene2; RNA types and levels of RNA structure; RNA structure prediction; genetic diversity; single nucleotide polymorphisms (SNPs), insertions and deletions; study and diagnosis of genetic variants; SNP databases; haplotypes and their analysis; prediction of genotype-phenotype associations, GWAS (Genome-Wide Association Studies). 8) Levels of protein structure; methods for determining macromolecular structures, including X-ray crystallography, nuclear magnetic resonance (NMR), and cryo-electron microscopy (cryo-EM); the Protein Data Bank (PDB); PDB format; molecular graphics software. 9) Structural classification of proteins; SCOP and CATH databases; the AlphaFold database; prediction of protein three-dimensional structure; molecular docking - objectives, significance, and principles; AutoDock, AutoDock Vina, and SwissDock software; molecular geometry; blind docking (Achilles server); prediction of protein-protein interactions; the PPI3D database; LightDock and Frodock software. 10) Bioinformatics in glycobiology; carbohydrate structures; protein glycosylation; N-glycans and O-glycans; the GAG-DB database; the concept of the carbohydrate code; information obtained from glycoprotein analysis; methods for glycan and glycoprotein analysis; enzymatic deglycosylation; GlycoMod, GlycoWorkbench, and SugarSketcher software.
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| Learning activities and teaching methods |
Monologic Lecture(Interpretation, Training), Dialogic Lecture (Discussion, Dialog, Brainstorming)
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| Learning outcomes |
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The course explains the theoretical and practical context of bioinformatics. It covers biological databases, sequence alignment, gene and protein structures, protein structure prediction, molecular phylogenetics, genomics, proteomics and glycobiology. Students will gain practical experience with bioinformatics tools and develop skills in collecting and presenting bioinformatics data.
Students will gain basic knowledge of bioinformatics, i.e. what it deals with, and will be introduced to bioinformatics tools and their application. |
| Prerequisites |
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successful passing of the subjects from the first three semesters of the study plan Bioinformatics (bachelor level), namely the subjects KMI/UDI and KBC/UBCH.
KBC/BCH ----- or ----- KBC/UBC ----- or ----- KBC/UBCH |
| Assessment methods and criteria |
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Written exam, Seminar Work
The lecture is supplemented by a seminar where tasks are solved under the supervision of the teacher, as well as homework and the requirement to complete an independent bioinformatics project. The written exam confirming knowledge of the taught subject is 1 hour long, 8 questions, maximum number of points 24. A: 24-22 points; B: 21-19 points; C: 18-16 points; D: 15-14 points; E: 13-12 points; F: less than 12 points. |
| Recommended literature |
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| Study plans that include the course |
| Faculty | Study plan (Version) | Category of Branch/Specialization | Recommended semester | |
|---|---|---|---|---|
| Faculty: Faculty of Science | Study plan (Version): Bioinformatics (2021) | Category: Informatics courses | 2 | Recommended year of study:2, Recommended semester: Summer |
| Faculty: Faculty of Science | Study plan (Version): Biochemistry (2026) | Category: Chemistry courses | 2 | Recommended year of study:2, Recommended semester: Summer |
| Faculty: Faculty of Science | Study plan (Version): Analytical Biochemist (2024) | Category: Chemistry courses | 1 | Recommended year of study:1, Recommended semester: Summer |
| Faculty: Faculty of Science | Study plan (Version): Teaching Training in Computer Science for Secondary Schools (2019) | Category: Pedagogy, teacher training and social care | 1 | Recommended year of study:1, Recommended semester: Summer |
| Faculty: Faculty of Science | Study plan (Version): Computer Science - Specialization in General Computer Science (2020) | Category: Informatics courses | 1 | Recommended year of study:1, Recommended semester: Summer |
| Faculty: Faculty of Science | Study plan (Version): Computer Science - Specialization in Artificial Intelligence (2020) | Category: Informatics courses | 1 | Recommended year of study:1, Recommended semester: Summer |
| Faculty: Faculty of Science | Study plan (Version): Applied Computer Science - Specialization in Computer Systems and Technologies (2024) | Category: Informatics courses | 1 | Recommended year of study:1, Recommended semester: Summer |
| Faculty: Faculty of Science | Study plan (Version): Applied Computer Science - Specialization in Software Development (2024) | Category: Informatics courses | 1 | Recommended year of study:1, Recommended semester: Summer |