|Name||Prof. Dr. Niko Beerenwinkel|
Professur f. Computational Biology
ETH Zürich, BSS G 57.2
|Telephone||+41 61 387 31 69|
|Department||Biosystems Science and Engineering|
|636-0009-00L||Evolutionary Dynamics||6 credits||2V + 1U + 2A||N. Beerenwinkel|
|Abstract||Evolutionary dynamics is concerned with the mathematical principles according to which life has evolved. This course offers an introduction to mathematical modeling of evolution, including deterministic and stochastic models, with an emphasis on tumor evolution.|
|Objective||The goal of this course is to understand and to appreciate mathematical models and computational methods that provide insight into the evolutionary process in general and tumor evolution in particular. Students should analyze and evaluate models and their application critically and be able to design new models.|
|Content||Evolution is the one theory that encompasses all of biology. It provides a single, unifying concept to understand the living systems that we observe today. We will introduce several types of mathematical models of evolution to describe gene frequency changes over time in the context of different biological systems, focusing on asexual populations. Viruses and cancer cells provide the most prominent examples of such systems and they are at the same time of great biomedical interest. The course will cover some classical mathematical population genetics and population dynamics, and also introduce several new approaches. This is reflected in a diverse set of mathematical concepts which make their appearance throughout the course, all of which are introduced from scratch. Topics covered include the quasispecies equation, evolution of HIV, evolutionary game theory, evolutionary stability, evolutionary graph theory, tumor evolution, stochastic tunneling, genetic progression of cancer, diffusion theory, fitness landscapes, branching processes, and evolutionary escape.|
|Literature||- Evolutionary Dynamics. Martin A. Nowak. The Belknap Press of Harvard University Press, 2006.|
- Evolutionary Theory: Mathematical and Conceptual Foundations. Sean H. Rice. Sinauer Associates, Inc., 2004.
|Prerequisites / Notice||Prerequisites: Basic mathematics (linear algebra, calculus, probability)|
|636-0301-00L||Current Topics in Biosystems Science and Engineering|
Does not take place this semester.
For doctoral students only.
Master's students cannot receive credits for the seminar.
|2 credits||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, S. Reddy, T. Schroeder, J. Stelling, B. Treutlein|
|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 https://www.bsse.ethz.ch/news-and-events/seminar-series.html|
|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, K. M. Borgwardt, D. Iber, M. H. Khammash, J. Stelling|
|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, 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.|
|636-1005-AAL||Bio V: Bioinformatics|
Enrolment ONLY for MSc students with a decree declaring this course unit as an additional admission requirement.
Any other students (e.g. incoming exchange students, doctoral students) CANNOT enrol for this course unit.
|5 credits||7R||N. Beerenwinkel|
|Literature||Pevsner J, Bioinformatics and Functional Genomics, 3rd edition, 2015, chapters 1–7|