Jörg Stelling: Catalogue data in Autumn Semester 2023 |
| Name | Prof. Dr. Jörg Stelling |
| Field | Computational Systems Biology |
| Address | Comput. Systems Biology, Stelling ETH Zürich, BSS H 19.1 Klingelbergstrasse 48 4056 Basel SWITZERLAND |
| Telephone | +41 61 387 31 94 |
| joerg.stelling@bsse.ethz.ch | |
| Department | Biosystems Science and Engineering |
| Relationship | Full Professor |
| Number | Title | ECTS | Hours | Lecturers | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 636-0007-00L | Computational Systems Biology  | 6 credits | 3V + 2U | J. Stelling | |||||||||||
| Abstract | Study of fundamental concepts, models and computational methods for the analysis of complex biological networks. Topics: Systems approaches in biology, biology and reaction network fundamentals, modeling and simulation approaches (topological, probabilistic, stoichiometric, qualitative, linear / nonlinear ODEs, stochastic), and systems analysis (complexity reduction, stability, identification). | ||||||||||||||
| Learning objective | The aim of this course is to provide an introductory overview of mathematical and computational methods for the modeling, simulation and analysis of biological networks. | ||||||||||||||
| Content | Biology has witnessed an unprecedented increase in experimental data and, correspondingly, an increased need for computational methods to analyze this data. The explosion of sequenced genomes, and subsequently, of bioinformatics methods for the storage, analysis and comparison of genetic sequences provides a prominent example. Recently, however, an additional area of research, captured by the label "Systems Biology", focuses on how networks, which are more than the mere sum of their parts' properties, establish biological functions. This is essentially a task of reverse engineering. The aim of this course is to provide an introductory overview of corresponding computational methods for the modeling, simulation and analysis of biological networks. We will start with an introduction into the basic units, functions and design principles that are relevant for biology at the level of individual cells. Making extensive use of example systems, the course will then focus on methods and algorithms that allow for the investigation of biological networks with increasing detail. These include (i) graph theoretical approaches for revealing large-scale network organization, (ii) probabilistic (Bayesian) network representations, (iii) structural network analysis based on reaction stoichiometries, (iv) qualitative methods for dynamic modeling and simulation (Boolean and piece-wise linear approaches), (v) mechanistic modeling using ordinary differential equations (ODEs) and finally (vi) stochastic simulation methods. | ||||||||||||||
| Lecture notes | http://www.csb.ethz.ch/education/lectures.html | ||||||||||||||
| Literature | U. Alon, An introduction to systems biology. Chapman & Hall / CRC, 2006. Z. Szallasi et al. (eds.), System modeling in cellular biology. MIT Press, 2010. B. Ingalls, Mathematical modeling in systems biology: an introduction. MIT Press, 2013 | ||||||||||||||
| 636-0102-10L | Advanced Bioengineering Only for Biotechnologie Master, Programme Regulations 2021 or doctoral students of D-BSSE. | 2 credits | 3S | S. Panke, Y. Benenson, P. S. Dittrich, M. Fussenegger, A. Hierlemann, A. Moor, M. Nash, R. Platt, S. Reddy, T. Schroeder, J. Stelling, B. Treutlein | |||||||||||
| Abstract | This course provides an overview of modern concepts of bioengineering across different levels of complexity, from single molecules to systems, microscaled reactors to production environments, and across different fields of applications | ||||||||||||||
| Learning objective | Students will be able to recognize major developments in bioengineering across different organisms and levels of complexity and be able to relate it to major technological and conceptual advances in the underlying sciences. | ||||||||||||||
| Content | Molecular and cellular engineering; Synthetic biology: Engineering strategies in biology; from single molecules to systems; downscaling bioengineering; Bioengineering in chemistry, pharmaceutical sciences, and diagnostics, personalized medicine. | ||||||||||||||
| Lecture notes | Handouts during class | ||||||||||||||
| Literature | Will be announced during the course | ||||||||||||||
| Competencies |
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| 636-0704-00L | Computational Biology and Bioinformatics Seminar  Number of participants limited to 30. The seminar is addressed primarily at students enrolled in the MSc CBB programme. Students of other ETH study programmes interested in this course need to ask the lecturer for permission to enrol in the course. The Seminar will be offered in autumn semester in Basel (involving professors and lecturers from the University of Basel) and in spring semester in Zurich (involving professors and lecturers from the University of Zurich). Professors and lecturers from ETH Zurich are involved in both semesters. | 2 credits | 2S | N. Beerenwinkel, D. Iber, M. H. Khammash, T. Stadler, J. Stelling, to be announced | |||||||||||
| 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, University of Basel and University of Zurich, 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. | ||||||||||||||