Available courses

The purpose of this course is to teach R statistical environment to be applied to transcriptome data analysis. After this course, the students will be able to use R for analyzing diverse data types from very different biological experiments focused on gene expression. The topics will introduce the theoretical aspects of the covered methodologies, and after that, assignments and activities will provide opportunities to explore the practical ways of performing the analyses.
 
You will learn how to use R for performing statistical analysis relevant for molecular biologists. You will learn how to perform simple sequence analysis with R. You will get an essential overview of biological network analysis and the highly popular enrichment analysis of gene lists. Additionally, the most prominent transcriptome analysis methods will be covered with medium to advanced level code examples and practices.
 

The purpose of this course to teach R statistical environment to be applied to high-throughput biological data. After this course, the students will be able to use R for analyzing diverse data types from high-throughput biological experiments with a strong focus on different transcriptomics methods. Half of the course is dedicated to the analysis of data from next-generation sequencing experiments. All the topics will introduce the theoretical aspects of the introduced methodologies, and after that, assignments and activities will provide opportunities to explore the practical ways of performing the analyses.

The purpose of this course to teach R statistical environment to be applied to biological data analysis. After this course, the students will be able to use R for analyzing diverse data types from very different biological experiments. The topics will introduce the theoretical aspects of the introduced methodologies, and after that, assignments and activities will provide opportunities to explore the practical ways of performing the analyses.


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