Course: Fundamentals of Bioinformatics

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Course title Fundamentals of Bioinformatics
Course code KBC/ZBINF
Organizational form of instruction Lecture + Seminar
Level of course Bachelor
Year of study not specified
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)
  • Šebela Marek, prof. Mgr. Dr.
  • Raus Martin, Mgr. Ph.D.
  • Škrabišová Mária, Mgr. Ph.D.
Course content
1) Introduction to bioinformatics and information resources definition of bioinformatics; historical and scientific context of bioinformatics; problems studied and solved with bioinformatics tools; database types (primary vs. secondary); data formats; relationship between DNA, RNA and protein; explanation of the significance of structural similarity and homology; retrieval of relevant genetic, genomic and proteomic information; scientific literature pertaining to topics of interest; resources available in PubMed 2) Working with sequences (nucleotides and amino acids) structure of genes and genomes; distinguishing between prokaryotic and eukaryotic genes; finding information about a specific gene; interpretation of a GenBank entry; examination of whole genomes; identifying errors in a DNA sequence; analysis of a DNA sequence (establishing GC content, counting words, internal repeats); finding ORFs, exons and introns; assembling sequence fragments; interpretation of a Swiss-Prot entry; description of primary protein structures and ORFs; protein structure databases and describing the information they contain; prediction of physical-chemical properties of a protein from its sequence; performing primary structure analysis of a protein; description of secondary structural features of proteins; finding known domains within a given protein 3) Sequence alignment and similarity search significance of sequence homology; interpretation of BLAST outputs; interpretation of expectation values; using BLASTP to compare proteins; using tBLASTn to compare protein with DNA sequences; adjusting BLAST parameters for more effective comparisons; using PSI-BLAST to discover related protein sequences; construction and interpretation dot plots for sequence comparison; description of alignment algorithms; using online tools to perform local alignment of protein sequences; using online tools to perform global alignment of protein sequences; description of practical uses for multiple alignments (MSA); gathering sequences for multiple MSA; using online tools to perform MSA; interpretation of MSA; practical use of MSA 4) Protein structures Explaining the significance of folding and three-dimensional protein structure; secondary structure prediction; finding structural analogs for a protein sequence; retrieval of three-dimensional protein structures from PDB; installation and configuration of protein structure viewing software; viewing and manipulation with protein structural models on a computer screen; description of structural elements of proteins: alpha helices, beta sheets, coils; protein structural classification using online tools 5) RNA structures, SNPs and haplotypes Definition of genomics and description of applications in this field of study; definition of SNPs (single nucleotide polymorphism") and description of their prevalence in the human genome; definition of haplotypes and explaining how they help in bioinformatic analysis; describe applications of SNP and haplotype analysis; retrieval and interpretation of SNP and haplotype data from a genome browser; description of RNA secondary structures; using online tools to retrieve and perform structural prediction on RNA sequences; description of different types of RNA, including miRNAs; using online tools to discover patterns that describe secondary RNA structures; using online tools to search for miRNAs in sequences 6) Phylogenetics and comparative genomics Definition of phylogeny and explaining how phylogenetic relationships can be established with bioinformatics; making an alignment using ClustalW of given FASTA sequences; estimation of distances between sequences; differentiation between orthologs, paralogs and xenologs; construct phylogenetic trees from ClustalW results; description of tree construction algorithms (UPGMA, Fitch, Neighbor-joining); construction of phylogenetic trees using Phylip 7) Bioinformatics in glycobiology structures of saccharides; database of glycoenzymes;

Learning activities and teaching methods
Monologic Lecture(Interpretation, Training), Dialogic Lecture (Discussion, Dialog, Brainstorming)
  • Preparation for the Exam - 70 hours per semester
  • Attendace - 26 hours per semester
Learning outcomes
The subject explains theoretical and practical aspects of bioinformatics. There are biological databases included as well as sequence alignment, gene and protein structures, protein structure prediction, molecular phylogenetics, genomics, proteomics and glycobiology. Students will get acquainted themselves with bioinformatic tools and they will develop skills in retrieval, processing and presentation of bioinformatic data. In addition, they become experienced in fundamental programming and script languages.
Students become competent in bioinformatics and will get acquainted with bioinformatic tools and their applications.
Prerequisites
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
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KBC/UBCH

Assessment methods and criteria
Written exam, Seminar Work

The lecture is supplementted with a seminar for solving tasks under supervision of the teacher, doing homeworks each week and a requirement for completing a final bioinformatic project. Students are obliged to pass 2 written examination tests in the seminar (60% of points for a successful passing).
Recommended literature
  • Baxevanis AD, Ouellette BFF. (2004). Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins. WileyBlackwell; 3rd Edition edition.
  • Bourne, P.E., Weissig, H. (2003). Structural bioinformatics. Wiley-Liss, Hobojem, NJ, USA.
  • Claverie J.-M., Notredame C. (2007). Bioinformatics for dummies.. Hoboken.
  • Gibas, Cynthia & Per Jambeck. (2001). Developing Bioinformatics Computer Skills. O'Reilly.
  • St. Clair, Caroline and Jonathan Visick. (2010). Exploring Bioinformatics: a Project-Based Approach. Jones & Bartlett.
  • von der Lieth, Claus-Wilhelm; Lütteke, Thomas and Frank, Martin (editors). (2009). Bioinformatics for Glycobiology and Glycomics: an Introduction. Wiley.
  • Xiong, J. (2006). Essential Bioinformatics. Cambridge Univesity Press.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Faculty: Faculty of Science Study plan (Version): Applied Computer Science - Specialization in Computer Systems and Technologies (2020) Category: Informatics courses 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): Biochemistry (2022) Category: Chemistry courses 2 Recommended year of study:2, Recommended semester: Summer
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): 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): Applied Computer Science - Specialization in Software Development (2020) Category: Informatics courses 1 Recommended year of study:1, Recommended semester: Summer