Module

Voraussetzungen

Inhalte

The focus will be on four fundamental problem areas: • Comparing sequences: Sequence alignment algorithms, Genome-scale approaches using index data structures, Alignment-free methods • Analyzing gene expression: alignment-based and alignment-free methods to analyzing RNASeq, single-cell analysis • Signals in sequences: identification of motifs, accessibility, and modification of DNA • Sequence variations and relation to phenotypes: structural variants in disease, pan-genome approaches

Lernziele

After successfully completing the module, students will have acquired an introduction to modern bioinformatics and to selected applications from biology and medicine. They understand the methodology through presentation of the central computational problems and an introduction of solutions based on classical algorithms and statistical machine learning, as well as modern deep learning approaches.

Prüfungsleistung

• Written examination, 120 min. OR • Oral examination, 30-45 min. (with small number of participants) In the first lecture it will be announced, the examination will be offered in written or oral form.

Bemerkungen

• Study programme Artificial Intelligence M.Sc.: Compulsory elective module in the complex „Knowledge Acquisition, Representation, and Processing” • Study programme Mathematical Data Science M.Sc.: Compulsory elective module in the complex „Data Science Applications”