|Name||Dr. Karsten Michael Borgwardt|
|Name variants||Karsten Borgwardt|
Karsten M. Borgwardt
Karsten Michael Borgwardt
ETH Zürich, D-BSSE, BSD G 234
|Telephone||+41 61 387 34 20|
|Department||Biosystems Science and Engineering|
|636-0018-00L||Data Mining I||6 credits||3G + 2A||K. M. Borgwardt|
|Abstract||Data Mining, the search for statistical dependencies in large databases, is of utmost important in modern society, in particular in biological and medical research. This course provides an introduction to the key problems, concepts, and algorithms in data mining, and the applications of data mining in computational biology.|
|Objective||The goal of this course is that the participants gain an understanding of data mining problems and algorithms to solve these problems, in particular in biological and medical applications.|
|Content||The goal of the field of data mining is to find patterns and statistical dependencies in large databases, to gain an understanding of the underlying system from which the data were obtained. In computational biology, data mining contributes to the analysis of vast experimental data generated by high-throughput technologies, and thereby enables the generation of new hypotheses.|
In this course, we will present the algorithmic foundations of data mining and its applications in computational biology. The course will feature an introduction to popular data mining problems and algorithms, reaching from classification via clustering to feature selection. This course is intended for both students who are interested in applying data mining algorithms and students who would like to gain an understanding of the key algorithmic concepts in data mining.
Tentative list of topics:
1. Distance functions
4. Feature Selection
|Lecture notes||Course material will be provided in form of slides.|
|Literature||Will be provided during the course.|
|Prerequisites / Notice||Basic understanding of mathematics, as taught in basic mathematics courses at the Bachelor's level.|
|636-0301-00L||Current Topics in Biosystems Science and Engineering|
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, A. Moor, D. J. Müller, S. Panke, S. Reddy, T. Schroeder, T. Stadler, 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|
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, T. Stadler, 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.|