Jörg Stelling: Katalogdaten im Frühjahrssemester 2017

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
KurzbeschreibungThe course teaches computational methods and first hands-on applications by starting from biological problems/phenomena that students in the 4th semester are somewhat familiar with. During the exercises, students will obtain first experience with programming their own analyses/models for data analysis/interpretation.
LernzielWe will teach little if any novel biological knowledge or analysis methods, but focus on training the ability of use existing knowledge (for example from enzyme kinetics, regulatory mechanisms or analytical methods) to understand biological problems that arise when considering molecular elements in their context and to translate some of these problems into a form that can be solved by computational methods. Specific goals are:
- understand the limitations of intuitive reasoning
- obtain a first overview of computational approaches in systems biology
- train ability to translate biological problems into computational problems
- solve practical problems by programming with MATLAB
- make first experiences in computational interpretation of biological data
- understand typical abstractions in modeling molecular systems
InhaltDuring the first 7 weeks, the will focus on mechanistic modeling. Starting from simple enzyme kinetics, we will move through the dynamics of small pathways that also include regulation and end with flux balance analysis of a medium size metabolic network. During the second 7 weeks, the focus will shift to the analysis of larger data sets, such as metabolomics and transcriptomics that are often generated in biology. Here we will go through multivariate statistical methods that include clustering and principal component analysis, ending with first methods to learn networks from data.
SkriptNo script
LiteraturThe course is not taught by a particular book, but two books are suggested for further reading:
- Systems Biology (Klipp, Herwig, Kowald, Wierling und Lehrach) Wiley-VCH 2009
- A First Course in Systems Biology (Eberhardt O. Voight) Garland Science 2012
626-0002-AALBioinformatics
Belegung ist NUR erlaubt für MSc Studierende, die diese Lerneinheit als Auflagenfach verfügt haben.

Alle anderen Studierenden (u.a. auch Mobilitätsstudierende, Doktorierende) können diese Lerneinheit NICHT belegen.
4 KP9RJ. Stelling, N. Beerenwinkel
KurzbeschreibungThe course introduces concepts of bioinformatics starting from first principles: DNA sequence alignment, phylogenetic tree inference, genome annotation, protein structure and function prediction. Key methods and algorithms are covered, including dynamic programming, Markov and Hidden Markov models, and molecular dynamics simulations. Practical applications and limitations are discussed.
LernzielThe course aims at introducing the fundamental concepts and methods of bioinformatics. Emphasis is given to a deep understanding of the methods' foundations and limitations to enable critical evaluations and applications of bioinformatics tools in areas such as biotechnology and systems biology.
InhaltFrom "Understanding Bioinformatics":
Chapter 4: Producing and Analyzing Sequence Alignments
Chapter 5: Pairwise Sequence Alignment and Database Searching
Chapter 6: Patterns, Profiles, and Multiple Alignments
Chapter 7: Recovering Evolutionary History
Chapter 8: Building Phylogenetic Trees
Chapter 9: Revealing Genome Features
Chapter 10: Gene Detection and Genome Annotation
Chapter 11: Obtaining Secondary Structure from Sequence
Chapter 12: Predicting Secondary Structures
Chapter 13: Modeling Protein Structure
Chapter 14: Analyzing Structure-Function Relationships

From "Biological Sequence Analysis":
Sections 3.1, 3.2, 3.3, 4.1, 4.2, 4.4, 5.2, 5.3, 5.4, 6.5 (Markov Chains and Hidden Markov Models)

From "A First Course in Systems Biology":
Chapter 1: Biological Systems
SkriptCourse material will be made available at: http://www.csb.ethz.ch
LiteraturZvelebil M, Baum JO. Understanding Bioinformatics. Garland Science, 2008.
Durbin R, Eddy S, Krogh A, Mitchinson G. Biological Sequence Analysis. Cambridge University Press, 2004.
Voit EO. A First Course in Systems Biology. Garland Science, 2012.
Voraussetzungen / BesonderesThere will be two opportunities for tutorials during the semester

http://www.csb.ethz.ch/teaching
636-0002-00LSynthetic Biology I Information 6 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 design.
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
636-0006-00LComputational Systems Biology: Deterministic Approaches Belegung eingeschränkt - Details anzeigen 6 KP3GJ. Stelling, D. Iber
KurzbeschreibungThe course introduces computational methods for systems biology under 'real-world' conditions of limiting biological knowledge, uncertain model scopes and predictions and spatial effects. The focus is on systems identification for mechanistic, deterministic models. Methods discussed include uncertainty evaluation, experimental design, abstract systems descriptions and spatially distributed 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, for example, in development and cellular signaling. Under all these conditions, a direct representation of biological mechanisms in mechanistic (ODE-based) mathematical models is impeded. Based on general concepts of systems identification, the course aims at providing complementary methods and algorithms that enable the analysis of mechanisms of biological operation in detail, using iterations between experimental and theoretical systems analysis.
InhaltLecture topics: (1) Mechanistic mathematical models and systems identification challenges; (2-4) Identification and experimental design for ordinary differential equation (ODE) models; (5-7) Structural analysis and approximate dynamic model; (8-9) Uncertainty quantification methods; (10-13) Spatial effects and partial differential equation (PDE) models
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 / BesonderesStudents are expected to have completed the courses 'Mathematical modeling for systems biology' (BSc Biotechnology) or 'Computational systems biology' (MSc Computational biology and bioinformatics), which provide the foundational knowledge for the course. http://www.csb.ethz/teaching
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, P. Pantazis, 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, N. Beerenwinkel, 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.