In this lecture, you will learn about fundamental algorithms and methods for the sequence and structure analysis of the biological macromolecule RNA. We start by discuss algorithms for predicting the RNA secondary structure (aka RNA folding) by maximizing base pairs and by minimizing energy. Then, we study the probabilistic analysis of structure by partition function approaches, which allow computing base pair probabilities. Furthermore, we look in depth at the comparison of RNAs by their sequence and structure, where we discuss the alignment of folded RNA as well as simultaneous alignment and folding. As special topics, we discuss RNA-RNA-interaction, as well as the algorithmic treatment of pseudoknots.
NOTE: The lecture will implement a
"flipped classroom" teaching format.
That is, most of the content is to be studied via self-learning modules BEFORE attending the lecture sessions. The lecture sessions are discussion forums that answer open questions and deepen the understanding of the material.
All course material (both for lecture and exercises)
and detailed session information
will be made available in the according course room
in the University's ILIAS platform linked below
RNA Bioinformatics course room at ILIAS