Matthias Gstaiger: Katalogdaten im Herbstsemester 2020 |
| Name | Herr Dr. Matthias Gstaiger |
| Adresse | Inst. f. Molekulare Systembiologie ETH Zürich, HPM F 43 Otto-Stern-Weg 3 8093 Zürich SWITZERLAND |
| Telefon | +41 44 633 34 49 |
| matthias.gstaiger@imsb.biol.ethz.ch | |
| Departement | Biologie |
| Beziehung | Dozent |
| Nummer | Titel | ECTS | Umfang | Dozierende | |
|---|---|---|---|---|---|
| 551-1299-00L | Introduction to Bioinformatics  | 6 KP | 4G | S. Sunagawa, M. Gstaiger, A. Kahles, G. Rätsch, B. Snijder, E. Vayena, C. von Mering, N. Zamboni | |
| Kurzbeschreibung | This course introduces principle concepts, the state-of-the-art and methods used in some major fields of Bioinformatics. Topics include: genomics, metagenomics, network bioinformatics, and imaging. Lectures are accompanied by practical exercises that involve the use of common bioinformatic methods and basic programming. | ||||
| Lernziel | The course will provide students with theoretical background in the area of genomics, metagenomics, network bioinformatics and imaging. In addition, students will acquire basic skills in applying modern methods that are used in these sub-disciplines of Bioinformatics. Students will be able to access and analyse DNA sequence information, construct and interpret networks that emerge though interactions of e.g. genes/proteins, and extract information based on computer-assisted image data analysis. Students will also be able to assess the ethical implications of access to and generation of new and large amounts of information as they relate to the identifiability of a person and the ownership of data. | ||||
| Inhalt | Ethics: Case studies to learn about applying ethical principles in human genomics research Genomics: Genetic variant calling Analysis and critical evaluation of genome wide association studies Metagenomics: Reconstruction of microbial genomes Microbial community compositional analysis Quantitative metagenomics Network bioinformatics: Inference of molecular networks Use of networks for interpretation of (gen)omics data Imaging: High throughput single cell imaging Image segmentation Automatic analysis of drug effects on single cell suspension (chemotyping) | ||||
| Voraussetzungen / Besonderes | Course participants have already acquired basic programming skills in Python and R. Students will bring and work on their own laptop computers, preferentially running the latest versions of Windows or MacOSX. | ||||