Module CS1400-KP04, CS1400
Introduction to Bioinformatics (EinBioinfo)
Duration
1 Semester
Turnus of offer
each winter semester
Credit points
4
Course of studies, specific fields and terms:
- Bachelor IT-Security 2016, optional subject, interdisciplinary
- Bachelor Nutritional Medicine 2024, compulsory, mathematics / computer science
- Bachelor Molecular Life Science 2024, compulsory, mathematics / computer science
- Bachelor MES 2020, optional subject, computer science / electrical engineering
- Bachelor Computer Science 2019, compulsory, Canonical Specialization Bioinformatics and Systems Biology
- Bachelor Computer Science 2019, optional subject, Introductory Module Computer Science
- Bachelor MLS 2018, compulsory, life sciences
- Bachelor MES 2014, optional subject, computer science / electrical engineering
- Bachelor Computer Science 2016, optional subject, Introductory Module Computer Science
- Bachelor Computer Science 2016, compulsory, Canonical Specialization Bioinformatics
- Bachelor MLS 2016, compulsory, life sciences
- Bachelor Medical Informatics 2014, compulsory, medical computer science
- Bachelor Computer Science 2014, compulsory, specialization field bioinformatics
- Bachelor Medical Informatics 2011, compulsory, medical computer science
- Bachelor MLS 2009, compulsory, life sciences
- Bachelor CLS 2010, compulsory, specialization field bioinformatics
- Bachelor MES 2011, optional subject, medical engineering science
- Bachelor Computer Science 2012, compulsory, specialization field bioinformatics
Classes and lectures:
- Introduction to Bioinformatics (lecture, 2 SWS)
- Introduction to Bioinformatics (exercise, 1 SWS)
Workload:
- 45 hours in-classroom work
- 20 hours exam preparation
- 55 hours private studies
Contents of teaching:
- Life, Evolution & the Genome
- Sequence assembly - Industrial reading of genetic information
- DNA sequence models & hidden markov models
- Viterbi-Algoritm
- Sequence alignment & dynamic programming
- Unsupervised data analysis (k-means, PCA, ICA)
- DNA microarrays & GeneChip technologies
Qualification-goals/Competencies:
- Students are able to explain the basic concepts of coding, transcription and translation of information in living beings.
- They are able to explain how a solution of the shortest common superstring problem can be estimated with a simple greedy algorithm.
- They are able to create a Markov chain or a Hidden Markov Model (HMM) for a given modelling problem.
- They are able to give examples on how to solve a problem using dynamic programming.
- They are able to implement the introduced algorithms (in Matlab)
- They are able to use unsupervised learning methods and they are able to interpret the results.
- They are able to explain basic Microarray-and DNA-Chip-Technologies.
Grading through:
- portfolio exam
Responsible for this module:
- Prof. Dr. rer. nat. Amir Madany Mamlouk
Teacher:
- Institute for Neuro- and Bioinformatics
- Prof. Dr. rer. nat. Amir Madany Mamlouk
Literature:
- H. Lodish, A. Berk, S. L. Zipursky and J. Darnell : Molekulare Zellbiologie Spektrum Akademischer Verlag, 4. Auflage, 2001, ISBN-13: 978-3827410771
- A. M. Lesk : Introduction to Bioinformatics Oxford University Press, 3. Auflage, 2008, ISBN-13: 978-0199208043
- R. Merkl and S. Waack : Bioinformatik Interaktiv: Grundlagen, Algorithmen, Anwendungen Wiley-VCH Verlag, 2. Auflage, 2009, ISBN-13: 978-3527325948
- M. S. Waterman : Introduction to Computational Biology Chapman and Hall, 1995
Language:
- offered only in German
Notes:
For students of the master programme Infection Biology, this is not a stand-alone module, but rather part of the module CS4011.Prerequisites for attending the module:
- None
Computer Science students get a B certificate.
Last Updated:
24.07.2023