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Lecturer(s)
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Piálek Lubomír, RNDr. Ing. Ph.D.
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Vlček Jakub, RNDr. Ph.D.
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Course content
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1.Bioinformatics - introduction, history, types of data and bioinformatics tools 2.Sanger sequencing, data visualization, primer design 3. Massively parallel sequencing (MPS), quality analysis 4. Homology in genetic data - alignment 5. Genetic databases and their use 6. Assembly of the genome and its annotation 7. Mapping MPS data to the reference genome 8. Searching for variable locations in mapped data - variant calling 9. Evaluation and filtering of genetic variants Content of tutorials/seminar: As part of the exercise, students will try the processing of genetic data itself using bioinformatics procedures. Each lecture is followed by an exercise that develops the lecture in a practical direction. 10. Polymorphism, estimation of population structure and history of populations 11. Reconstruction of family relationships 12. Modern trends in bioinformatics - golden rules and the influence of artificial intelligence
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Learning activities and teaching methods
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unspecified
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Learning outcomes
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The aim of the subject is to understand basic bioinformatics procedures using the example of processing large genetic data.
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Prerequisites
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A basic knowledge of computer work, genetics and mathematics is assumed.
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Assessment methods and criteria
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unspecified
credit: participation in practical exercises (maximum of two absences) exam: written (in the form of a test), the requirement for the exam is the fulfillment of credit
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Recommended literature
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Bioinformatics data skills, Vince Buffalo, O'Reilly 2015.
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Bioinformatics for High Throughput Sequencing, N. Rodriguez-Ezpeleta et al., Springer 2012.
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Practical bioinformatics for beginners, Low & Tammi 2023.
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Practical computing for biologists, S. Haddock & C. Dunn, Sinauer 2011.
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Úvod do praktické bioinformatiky, F. Cvrckova, 2006.
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