| Course Unit Code | 460-4143/01 |
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| Number of ECTS Credits Allocated | 4 ECTS credits |
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| Type of Course Unit * | Optional |
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| Level of Course Unit * | Second Cycle |
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| Year of Study * | Second Year |
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| Semester when the Course Unit is delivered | Winter Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | Czech |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| VAS218 | Ing. Michal Vašinek, Ph.D. |
| Summary |
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In the course, students will get acquainted with the basic approaches, methods and algorithms in bioinformatics.
Lectures will provide the necessary amount of theory so that it can be applied in students' independent work on exercises.
The exercises will offer a space for discussing the issue, a demonstration of practical tasks and exercises on simple assignments. |
| Learning Outcomes of the Course Unit |
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The graduate of the course will gain the following knowledge and skills:
theoretical foundations of bioinformatics,
implementation and application of selected methods for DNA, RNA and protein analysis. |
| Course Contents |
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Lectures:
1) Introduction to the principles of functioning of organisms at the DNA level
2) Sequence similarity
3) Data structures
4) Alignment
5) Genome assembly
6) Algorithms for searching in biological databases
7) Prediction of genes
8) Principles of technologies in the analysis of biological data
9) Detection of variants
10) Gene expression
11) Statistical methods for gene expression analysis
12) Phylogenetic data analysis
Exercises in the computer lab:
1) Practicing basic concepts for working with DNA
2) Practicing algorithms for calculating sequence similarity
3) Algorithms for construction of suffix trees
4) Practicing algorithms for global and local alignment
5) Practicing algorithms for genome assembly
6) Access to BLAST databases and practice of algorithms for searching in biological databases
7) Practicing the concepts needed for gene prediction
8) Getting acquainted with various representations of biological data
9) Practicing the concepts needed for the detection of variants
10) Practicing the concepts needed for gene expression
11) Practice of statistical analysis of gene expression data
12) Practicing algorithms for creating evolutionary trees |
| Recommended or Required Reading |
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| Required Reading: |
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1) Wing-Kin Sung. Algorithms in Bioinformatics: A Practical Introduction. Chapman & Hall/CRC Mathematical & Computational Biology. 2009
2) Arthur Lesk. Introduction to Bioinformatics. Oxford University Press, 2014.
3) Fatima Cvrčková. Úvod do praktické bioinformatiky. 1. vyd. Praha: Academia, 2006.
4) Pierre Baldi;G. Wesley Hatfield. DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling. Cambridge University Press 2002. |
1) Wing-Kin Sung. Algorithms in Bioinformatics: A Practical Introduction. Chapman & Hall/CRC Mathematical & Computational Biology. 2009
2) Arthur Lesk. Introduction to Bioinformatics. Oxford University Press, 2014.
3) Fatima Cvrčková. Úvod do praktické bioinformatiky. 1. vyd. Praha: Academia, 2006.
4) Pierre Baldi;G. Wesley Hatfield. DNA Microarrays and Gene Expression: From Experiments to Data Analysis and Modeling. Cambridge University Press 2002. |
| Recommended Reading: |
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| 1) Caroline St. Clair, Jonathan E. Visick. Exploring Bioinformatics: A Project-Based Approach. Jones & Bartlett Learning, 2013. |
| 1) Caroline St. Clair, Jonathan E. Visick. Exploring Bioinformatics: A Project-Based Approach. Jones & Bartlett Learning, 2013. |
| Planned learning activities and teaching methods |
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| Lectures, Tutorials |
| Assesment methods and criteria |
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| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
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| Graded credit | Graded credit | 100 (100) | 51 |
| Semestrální projekt | Semestral project | 40 | 0 |
| Vyhotovení úloh na cvičení | Other task type | 60 | 0 |