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Lecturer(s)
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Žlábek Vladimír, doc. Ing. Ph.D.
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Burkina Viktoriia, MSc. Ph.D.
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Gazo Ievgeniia, MSc. Ph.D.
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Urban Jan, Ing. Ph.D.
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Course content
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Basic topics of the course are: 1) Omics Techniques and Data Analysis - Intro 2) Genomics 3) Transcriptomics 4) Proteomics 5) Lipidomics 6) Metabolomics_MS 7) Metabolomics_NMR 8) Epigenomics 9) Metagenomics 10) Bioinformatics
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Individual tutoring
- Class attendance
- 20 hours per semester
- Semestral paper
- 8 hours per semester
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Learning outcomes
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The students will learn the basic principles of high-performance -omics technologies, generated data management, and the principles of choosing the most appropriate analysis method dependent on the defined problem. The aim of the course is to provide students with basic knowledge of Genomics, Transcriptomics, Proteomics, Lipidomics, Metabolomics, Metagenomics, Epigenomics, Biostatistics and present examples of applications in contemporary research. Course graduates will be able to evaluate the merits of the approach-creating hypothesis and complement the experiment appropriately with conventional analyses. The students will understand the principles of pre-processing, statistical analysis and visualization of large data sets necessary for the successful interpretation of experimental results generated by high-performance omics methods.
Study prerequisites includes basic knowledge of molecular biology and statistics.
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Prerequisites
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Study prerequisites includes basic knowledge of molecular biology and statistics.
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Assessment methods and criteria
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Combined exam, Test
Study prerequisites includes basic knowledge of molecular biology and statistics.
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Recommended literature
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Arivaradarajan, P., Misra, G. Omics Approaches, Technologies And Applications. Springer Verlag, Singapore, 2019. ISBN 9789811329241.
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Debmalya B., Vasudeo Z., Vasco A.. OMICS: Applications in Biomedical, Agricultural, and Environmental Sciences,. CRC Press, 2017. ISBN 9781138074750.
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