Dagmar Iber: Catalogue data in Spring Semester 2018 |  |
| Name | Prof. Dr. Dagmar Iber |
| Field | Computational Biology |
| Address | Professur f. Computational Biology ETH Zürich, D-BSSE, BSD G 204.2 Mattenstrasse 26 4058 Basel SWITZERLAND |
| Telephone | +41 61 387 32 10 |
| dagmar.iber@bsse.ethz.ch | |
| URL | http://www.bsse.ethz.ch/cobi |
| Department | Biosystems Science and Engineering |
| Relationship | Associate Professor |
| Number | Title | ECTS | Hours | Lecturers | |
|---|---|---|---|---|---|
| 636-0006-00L | Computational Systems Biology: Deterministic Approaches  | 4 credits | 3G | J. Stelling, D. Iber | |
| Abstract | The course introduces computat. methods for systems biology under ‘real-world’ conditions of limiting biological knowledge, uncertain model scopes and predictions, and spatial effects. Focus is on systems identification for mechanistic, deterministic models and the corresponding numerical approaches. Topics include uncertainty evaluation, experim. design, and numerical methods for spatial models | ||||
| Objective | The aim of the course is to provide students with mathematical and computational methods for the analysis of biological systems in a ‘real world’ setting. This implies (i) incomplete knowledge of components, interactions, and their quantitative features in cellular networks, (ii) resulting uncertainties in model predictions and iterations between models and experiments, and (iii) spatial effects. All these factors make direct representations of biological mechanisms in mechanistic, deterministic mathematical models challenging. Based on general concepts of systems identification and on corresponding numerical methods, the course aims at providing an in-depth understanding of computational approaches that enable the analysis of mechanisms of biological network operation in detail, using iterations between experimental and theoretical systems analysis. | ||||
| Content | Lecture topics: (1) Mechanistic mathematical models and systems identification challenges; (2-4) Structural models and data integration; (5-8) Identification and experimental design for ODE models; (9-10) Uncertainty quantification; (11-13) Numerical methods for partial differential equation (PDE) models to describe spatial effects. | ||||
| Lecture notes | Course material will be made available at: http://www.csb.ethz.ch | ||||
| Literature | Background literature will be available on-line at the start of the course. | ||||
| Prerequisites / Notice | For this advanced course, participants are expected to have a solid background in the mathematical modelling of biological systems, as conveyed by the combination of the following two courses in the MSc Computational Biology and Bioinformatics: ‘Computational systems biology’ and ‘Spatio-temporal modeling in biology’. | ||||
| 636-0301-00L | Current Topics in Biosystems Science and Engineering | 2 credits | 1S | T. Stadler, N. Beerenwinkel, Y. Benenson, K. M. Borgwardt, P. S. Dittrich, M. Fussenegger, A. Hierlemann, D. Iber, M. H. Khammash, D. J. Müller, S. Panke, R. Paro, R. Platt, S. Reddy, T. Schroeder, J. Stelling | |
| Abstract | This seminar will feature invited lectures about recent advances and developments in systems biology, including topics from biology, bioengineering, and computational biology. | ||||
| Objective | To provide an overview of current systems biology research. | ||||
| Content | The final list of topics will be available at http://www.bsse.ethz.ch/education/. | ||||
| 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. | ||||
| 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. | ||||