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CS 594 — Algorithms in Bioinformatics
(dt. Algorithmische Bioinformatik)

Level, degree of commitment Specialization 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: Written or oral examination (individual examination)
Language,
Grading		 English,
The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Computer Science.
Duration,
frequency		 One semester,
Regelmäßig alle 2 Semester
Person in charge of the module's outline Prof. Dr. Dominik Heider

Contents

  • Biological basics
  • DNA analysis and gene detection
  • Microarray techniques and analysis
  • Visualization and dimension reduction
  • Genes Ontologies
  • overrepresentation analysis
  • Micro-RNAs and their functions
  • Knowledge discovery in biological knowledge bases

Qualification Goals

Students will

  • understand basic issues and goals in bioinformatics,
  • know basic concepts of DNA and protein modeling,
  • have knowledge of algorithmic principles of bioinformatics applications,
  • understand methods of knowledge discovery in biological databases and are able to apply them,
  • are able to apply scientific working methods when independently identifying, formulating and solving problems,
  • are able to speak freely about scientific content, both in front of an audience and in a discussion.

Prerequisites

None. Basic knowledge in the scope of the module Introduction to Computer Science is recommended. Biological basics will be recapitulated, therefore no previous knowledge is required.


Applicability

Module imported from M.Sc. Computer Science.

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

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

When studying B.Sc. Data Science, this module can be attended in the study area Free Compulsory Elective Modules.

The module is assigned to Computer Science. Further information on eligibility can be found in the description of the study area.


Recommended Reading

  • J. Xiong. Essential Bioinformatics. Cambridge University Press, 2006.
  • W. W. Cohen. A Computer Scientist’s Guide to Cell Biology. Springer-Verlag, 2007.
  • N. Cristianini, M.W. Hahn. Introduction to Computational Genomics – A case studies approach. Cambridge press, 2007.
  • F. J. Burkowski. Structural Bioinformatics – An algorithmic approach. Chapman & Hall, CRC, 2009..



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2023/24. 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.