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This entry is from Winter semester 2018/19 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): Written or oral examination Examination type: Successful completion of at least 50 percent of the points from the weekly exercises as well as at least 2 presentations of the tasks. |
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
Translation is missing. Here is the German original:
Keine. Empfohlen werden Grundkenntnisse im Umfang des Moduls Einführung in die Informatik. Biologische Grundlagen werden rekapituliert, entsprechende Vorkenntnisse daher nicht vorausgesetzt.
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 M.Sc. Data Science, this module can be attended in the study area Specialization 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 2018/19. 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:
- Winter 2016/17
- Summer 2018
- Winter 2018/19
- Winter 2019/20
- Winter 2020/21
- Summer 2021
- Winter 2021/22
- Winter 2022/23
- Winter 2023/24
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.