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FEKT-MPA-SYSAcad. year: 2024/2025
The course is oriented to gain knowledge of methods used in systems biology, creating models of cellular organisms and possibilities of their usage. It aims on computational methods used to describe behavior of living organisms on molecular level that are utilizable in cellular biology, biochemistry, and biotechnology.Studied models are represented by extensive network graphs. Special attention is paid to both methodologies of model analysis, static as well as dynamic, especially using quantitative ODE models. The concept of hierarchy is followed and all functional layers, from gene regulatory network to signaling pathways and metabolic networks, are presented. Examples of models are given on systems of particular, especially unicellular, organisms.
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Offered to foreign students
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specialization NGRI , 0 year of study, summer semester, electivespecialization NADE , 0 year of study, summer semester, electivespecialization NISD , 0 year of study, summer semester, electivespecialization NMAT , 0 year of study, summer semester, electivespecialization NSEC , 0 year of study, summer semester, electivespecialization NISY up to 2020/21 , 0 year of study, summer semester, electivespecialization NNET , 0 year of study, summer semester, electivespecialization NMAL , 0 year of study, summer semester, electivespecialization NCPS , 0 year of study, summer semester, electivespecialization NHPC , 0 year of study, summer semester, electivespecialization NVER , 0 year of study, summer semester, electivespecialization NIDE , 0 year of study, summer semester, electivespecialization NISY , 0 year of study, summer semester, electivespecialization NEMB , 0 year of study, summer semester, electivespecialization NSPE , 0 year of study, summer semester, electivespecialization NEMB , 0 year of study, summer semester, electivespecialization NBIO , 0 year of study, summer semester, electivespecialization NSEN , 0 year of study, summer semester, electivespecialization NVIZ , 0 year of study, summer semester, elective
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Exercise in computer lab