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.
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.