Manfred Claassen: Catalogue data in Spring Semester 2018 |
| Name | Prof. Dr. Manfred Claassen |
| Field | Computational Biology |
| Address | Lehre Biologie ETH Zürich, HPM H 26 Otto-Stern-Weg 3 8093 Zürich SWITZERLAND |
| claassen@imsb.biol.ethz.ch | |
| Department | Biology |
| Relationship | Lecturer |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 551-0324-00L | Systems Biology | 6 credits | 4V | R. Aebersold, B. Christen, M. Claassen, U. Sauer | |
| Abstract | Introduction to experimental and computational methods of systems biology. By using baker’s yeast as a thread through the series, we focus on global methods for analysis of and interference with biological functions. Illustrative applications to other organisms will highlight medical and biotechnological aspects. | ||||
| Learning objective | - obtain an overview of global analytical methods - obtain an overview of computational methods in systems biology - understand the concepts of systems biology | ||||
| Content | Overview of global analytical methods (e.g. DNA arrays, proteomics, metabolomics, fluxes etc), global interference methods (siRNA, mutant libraries, synthetic lethality etc.) and imaging methods. Introduction to mass spectrometry and proteomics. Concepts of metabolism in microbes and higher cells. Systems biology of developmental processes. Concepts of mathematical modeling and applications of computational systems biology. | ||||
| Lecture notes | no script | ||||
| Literature | The course is not taught by a particular book, but some books are suggested for further reading: - Systems biology in Practice by Klipp, Herwig, Kowald, Wierling und Lehrach. Wiley-VCH 2005 | ||||
| 551-0362-00L | Analysis of Signaling Networks by Mass Spectrometry  Number of participants limited to 10. The enrolment is done by the D-BIOL study administration. | 6 credits | 7G | M. Gstaiger, M. Claassen, B. Wollscheid | |
| Abstract | This course provides the theoretical and practical basis for the biochemical and computational analysis of signaling networks using quantitative mass spectrometry and advanced statistical methods. | ||||
| Learning objective | In this course we will introduce basic and emerging techniques to study dynamic signalling networks using state of the art quantitative mass spectrometry techniques. This will involve the systematic characterization of signaling networks by affinity purification and phospho-peptide enrichment combined with quantitative mass spectrometry. We will also introduce and apply computational tools for statistical analysis, data visualization and network inference to build new hypothesis on the basis of the obtained data. | ||||
| Prerequisites / Notice | This course requires a basic knowledge in mass spectrometry based proteomics and experience in computational data processing using R or MatLab. Ideally this course should be combined with course 551-0352-00L "Protein Analysis by Mass Spectrometry". | ||||
| 636-0704-00L | Computational Biology and Bioinformatics Seminar | 2 credits | 2S | J. Stelling, M. Claassen, G. H. Gonnet, D. Iber, T. Stadler | |
| Abstract | Computational biology and bioinformatics aim at an understanding of living systems through computation. The seminar combines student presentations and current research project presentations to review the rapidly developing field from a computer science perspective. Areas: DNA sequence analysis, proteomics, optimization and bio-inspired computing, and systems modeling, simulation and analysis. | ||||
| Learning objective | Studying and presenting fundamental papers of Computational Biology and Bioinformatics. Learning how to make a scientific presentation and how classical methods are used or further developed in current research. | ||||
| Content | Computational biology and bioinformatics aim at advancing the understanding of living systems through computation. The complexity of these systems, however, provides challenges for software and algorithms, and often requires entirely novel approaches in computer science. The aim of the seminar is to give an overview of this rapidly developing field from a computer science perspective. In particular, it will focus on the areas of (i) DNA sequence analysis, sequence comparison and reconstruction of phylogenetic trees, (ii) protein identification from experimental data, (iii) optimization and bio-inspired computing, and (iv) systems analysis of complex biological networks. The seminar combines the discussion of selected research papers with a major impact in their domain by the students with the presentation of current active research projects / open challenges in computational biology and bioinformatics by the lecturers. Each week, the seminar will focus on a different topic related to ongoing research projects at ETHZ, thus giving the students the opportunity of obtaining knowledge about the basic research approaches and problems as well as of gaining insight into (and getting excited about) the latest developments in the field. | ||||
| Literature | Original papers to be presented by the students will be provided in the first week of the seminar. | ||||