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This entry is from Winter semester 2020/21 and might be obsolete. You can find a current equivalent here.

CS 541 — Introduction to Bioinformatics
(dt. Einführung in die Bioinformatik)

Level, degree of commitment Advanced module, compulsory elective module
Forms of teaching and learning,
workload		 Lecture (2 SWS), recitation class (2 SWS),
180 hours (60 h attendance, 120 h private study)
Credit points,
formal requirements		 6 CP
Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises as well as at least 2 presentations of the tasks.
Examination type: Oral or written examination
Language,
Grading		 German,
The grading is done with 0 to 15 points according to the examination regulations for the degree program B.Sc. Computer Science.
Duration,
frequency		 One semester,
Regelmäßig alle 2 Semester
Person in charge of the module's outline Prof. Dr. Dominik Heider

Contents

Selected bioinformatic methods required for calculations in the natural sciences, in particular from the field of biological databases (e.g. NCBI, Swissprot), algorithms for sequence alignments (e.g. Needleman-Wunsch, Smith-Waterman, ClustalW, BLAST), phylogenetic reconstruction, as well as methods from the field of structural bioinformatics (e.g. pymol, docking). The methods are presented in the lecture. During the exercise, their application will be practiced using concrete case studies.


Qualification Goals

The students are familiar with the most important bioinformatic methods required for calculations in the natural sciences. They have understood these methods and are able to select and carry out suitable bioinformatic procedures for concrete case studies.


Prerequisites

None. The competences taught in the following modules are recommended: either Algorithms and Data Structures or Practical Informatics II: Data Structures and Algorithms for Pre-Service-Teachers.


Applicability

Module imported from B.Sc. Computer Science.

It can be attended at FB12 in study program(s)

  • B.Sc. Data Science
  • B.Sc. Computer Science
  • B.Sc. Mathematics
  • M.Sc. Data Science
  • M.Sc. Computer Science
  • M.Sc. Mathematics
  • LAaG Computer Science

When studying M.Sc. Data Science, this module can be attended in the study area Specialization Modules in Computer Science.


Recommended Reading

  • Selzer, Marhöfer, Rohwer: Applied Bioinformatics, Springer
  • Weitere Literatur wird in der Lehrveranstaltung bekanntgegeben.



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2020/21. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.