Jörg Stelling: Katalogdaten im Frühjahrssemester 2018

NameHerr Prof. Dr. Jörg Stelling
LehrgebietRechnergestützte Systembiologie
Adresse
Comput. Systems Biology, Stelling
ETH Zürich, BSS H 19.1
Klingelbergstrasse 48
4056 Basel
SWITZERLAND
Telefon+41 61 387 31 94
E-Mailjoerg.stelling@bsse.ethz.ch
DepartementBiosysteme
BeziehungOrdentlicher Professor

NummerTitelECTSUmfangDozierende
551-1174-00LSystembiologie4 KP2V + 2UU. Sauer, K. M. Borgwardt, J. Stelling, N. Zamboni
KurzbeschreibungAusgehend von biologischen Fragen und Phänomenen unterrichtet der Kurs zur Beantwortung notwendige Konzepte von Modellierungen und Datenanalysen. In den Übungen erhalten die Studenten erste praktische Erfahrungen in einfacher Programmierung eigener Modelle und Analysen.
LernzielWir unterrichten kein oder nur wenig neues biologisches Wissen oder experimentelle Analysemethoden, sondern nutzen aus dem Studium bekanntes Wissen (z. B. Enzymkinetik, Regulationsmechanismen oder analytische Methoden). Unser Ziel ist es biologische Probleme aufzuzeigen, die aus dynamischen Interaktionen molekularer Elemente entstehen und mit Hilfe von Computermethoden gelöst werden können. Spezifische Ziele sind:
- Verständnis der Limitationen intuitiver Argumentation in der Biologie
- Ein erster Überblick über Computermethoden in der Systembiologie
- Übersetzen biologischer Fragestellungen in computerlösbare Probleme
- Praktische Erfahrungen in Programmierung mit MATLAB
- Erste Erfahrungen in der Computerinterprätation von biologischen Daten
- Verständnis typischer Abstraktionen in der Modellierung molekularer Systeme
InhaltWährend der ersten 7 Wochen konzentrieren wir uns auf mechanistische Modellierungen. Ausgehend von einfachen Enzymkinetiken betrachten wir zunächst die Dynamik von kleinerer Stoffwechselwegen und enden mit stöchiometrischen Modellen mittlerer Netzwerke. In der zweiten Kurshälfte konzentrieren wir uns auf die Analyse von typischen biologischen Omics Datensätzen. Wir starten mit multivariaten statistischen Methoden wie z. B. Clustering und Principal Component Analysis und enden mit Methoden um Netzwerke aus Daten zu lernen.
SkriptNo script
LiteraturDer Kurs wird nicht mit einem bestimmten Lehrbuch unterrichtet, aber 2 Bücher werden zur Unterstützung empfohlen:
- Systems Biology (Klipp, Herwig, Kowald, Wierling und Lehrach) Wiley-VCH 2009
- A First Course in Systems Biology (Eberhardt O. Voight) Garland Science 2012
636-0006-00LComputational Systems Biology: Deterministic Approaches Belegung eingeschränkt - Details anzeigen 4 KP3GJ. Stelling, D. Iber
KurzbeschreibungThe 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
LernzielThe 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.
InhaltLecture 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.
SkriptCourse material will be made available at: http://www.csb.ethz.ch
LiteraturBackground literature will be available on-line at the start of the course.
Voraussetzungen / BesonderesFor 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’.
636-0111-00LSynthetic Biology I
Attention: This course was offered in previous semesters with the number: 636-0002-00L "Synthetic Biology I". Students that already passed course 636-0002-00L cannot receive credits for course 636-0111-00L.
4 KP3GS. Panke, J. Stelling
KurzbeschreibungTheoretical & practical introduction into the design of dynamic biological systems at different levels of abstraction, ranging from biological fundamentals of systems design (introduction to bacterial gene regulation, elements of transcriptional & translational control, advanced genetic engineering) to engineering design principles (standards, abstractions) mathematical modelling & systems desig
LernzielAfter the course, students will be able to theoretically master the biological and engineering fundamentals required for biological design to be able to participate in the international iGEM competition (see www.syntheticbiology.ethz.ch).
InhaltThe overall goal of the course is to familiarize the students with the potential, the requirements and the problems of designing dynamic biological elements that are of central importance for manipulating biological systems, primarily (but not exclusively) prokaryotic systems. Next, the students will be taken through a number of successful examples of biological design, such as toggle switches, pulse generators, and oscillating systems, and apply the biological and engineering fundamentals to these examples, so that they get hands-on experience on how to integrate the various disciplines on their way to designing biological systems.
SkriptHandouts during classes.
LiteraturMark Ptashne, A Genetic Switch (3rd ed), Cold Spring Haror Laboratory Press
Uri Alon, An Introduction to Systems Biology, Chapman & Hall
Voraussetzungen / Besonderes1) Though we do not place a formal requirement for previous participation in particular courses, we expect all participants to be familiar with a certain level of biology and of mathematics. Specifically, there will be material for self study available on http://www.bsse.ethz.ch/bpl/education/index as of mid January, and everybody is expected to be fully familiar with this material BEFORE THE CLASS BEGINS to be able to follow the different lectures. Please contact sven.panke@bsse.ethz.ch for access to material
2) The course is also thought as a preparation for the participation in the international iGEM synthetic biology summer competition (www.syntheticbiology.ethz.ch, http://www.igem.org). This competition is also the contents of the course Synthetic Biology II. http://www.bsse.ethz.ch/bpl/education/index
636-0301-00LCurrent Topics in Biosystems Science and Engineering2 KP1ST. 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
KurzbeschreibungThis seminar will feature invited lectures about recent advances and developments in systems biology, including topics from biology, bioengineering, and computational biology.
LernzielTo provide an overview of current systems biology research.
InhaltThe final list of topics will be available at http://www.bsse.ethz.ch/education/.
636-0704-00LComputational Biology and Bioinformatics Seminar2 KP2SJ. Stelling, M. Claassen, G. H. Gonnet, D. Iber, T. Stadler
KurzbeschreibungComputational 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.
LernzielStudying 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.
InhaltComputational 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.
LiteraturOriginal papers to be presented by the students will be provided in the first week of the seminar.