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This entry is from Winter semester 2019/20 and might be obsolete. You can find a current equivalent here.

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
Language,
Grading		 German,
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. Alfred Ultsch

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

The students shall

  • understand basic questions and goals in bioinformatics,
  • know the basic concepts of DNA and protein modelling,
  • acquire knowledge of the algorithmic basics of bioinformatic applications,
  • understand and apply methods of knowledge discovery in biological databases,
  • practice scientific working methods (recognizing, formulating, solving problems, training the ability to abstract),
  • practice oral communication skills in the exercises by practicing free speech in front of an audience.

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 Compulsory Elective Modules in Computer Science.


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 2019/20. 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.