## Jörg Stelling: Katalogdaten im Herbstsemester 2018 |

Name | Herr Prof. Dr. Jörg Stelling |

Lehrgebiet | Rechnergestützte Systembiologie |

Adresse | Comput. Systems Biology, Stelling ETH Zürich, D-BSSE, BSA N 800 Mattenstrasse 26 4058 Basel SWITZERLAND |

Telefon | +41 61 387 31 94 |

joerg.stelling@bsse.ethz.ch | |

Departement | Biosysteme |

Beziehung | Ordentlicher Professor |

Nummer | Titel | ECTS | Umfang | Dozierende | |
---|---|---|---|---|---|

636-0007-00L | Computational Systems Biology | 6 KP | 3V + 2U | J. Stelling | |

Kurzbeschreibung | 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). | ||||

Lernziel | 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. | ||||

Inhalt | 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. | ||||

Skript | http://www.csb.ethz.ch/education/lectures.html | ||||

Literatur | 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 | ||||

636-0301-00L | Current Topics in Biosystems Science and EngineeringFor doctoral students only. Master's students cannot receive credits for the seminar. | 2 KP | 1S | R. Platt, 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, S. Reddy, T. Schroeder, T. Stadler, J. Stelling | |

Kurzbeschreibung | This seminar will feature invited lectures about recent advances and developments in systems biology, including topics from biology, bioengineering, and computational biology. | ||||

Lernziel | To provide an overview of current systems biology research. | ||||

Inhalt | The final list of topics will be available at https://www.bsse.ethz.ch/news-and-events/seminar-series.html | ||||

636-0507-00L | Synthetic Biology II Students in the MSc Programme Biotechnology (Programme Regulation 2017) may select Synthetic Biology II instead of the Research Project 1. | 8 KP | 4A | S. Panke, Y. Benenson, J. Stelling | |

Kurzbeschreibung | 7 months biological design project, during which the students are required to give presentations on advanced topics in synthetic biology (specifically genetic circuit design) and then select their own biological system to design. The system is subsequently modeled, analyzed, and experimentally implemented. Results are presented at an international student competition at the MIT (Cambridge). | ||||

Lernziel | The students are supposed to acquire a deep understanding of the process of biological design including model representation of a biological system, its thorough analysis, and the subsequent experimental implementation of the system and the related problems. | ||||

Inhalt | Presentations on advanced synthetic biology topics (eg genetic circuit design, adaptation of systems dynamics, analytical concepts, large scale de novo DNA synthesis), project selection, modeling of selected biological system, design space exploration, sensitivity analysis, conversion into DNA sequence, (DNA synthesis external,) implementation and analysis of design, summary of results in form of scientific presentation and poster, presentation of results at the iGEM international student competition (www.igem.org). | ||||

Skript | Handouts during course | ||||

Voraussetzungen / Besonderes | The final presentation of the project is typically at the MIT (Cambridge, US). Other competing schools include regularly Imperial College, Cambridge University, Harvard University, UC Berkeley, Princeton Universtiy, CalTech, etc. This project takes place between end of Spring Semester and beginning of Autumn Semester. Registration in April. Please note that the number of ECTS credits and the actual work load are disconnected. | ||||

636-0704-00L | Computational Biology and Bioinformatics SeminarThe Seminar will be offered in autumn semester in Basel and in spring semester in Zürich. | 2 KP | 2S | N. Beerenwinkel, M. Claassen, D. Iber, T. Stadler, J. Stelling | |

Kurzbeschreibung | Computational Biology und Bioinformatik analysieren lebende Systeme mit Methoden der Informatik. Das Seminar kombiniert Präsentationen von Studierenden und Forschenden, um das sich schnell entwickelnde Gebiet aus der Informatikperspektive zu skizzieren. Themenbereiche sind Sequenzanalyse, Proteomics, Optimierung und Bio-inspired computing, Systemmodellierung, -simulation und -analyse. | ||||

Lernziel | 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. | ||||

Inhalt | 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. | ||||

Literatur | Original papers to be presented by the students will be provided in the first week of the seminar. |