Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
Please read the published information on the individual courses carefully.

Karsten M. Borgwardt: Catalogue data in Autumn Semester 2018

Name Prof. Dr. Karsten M. Borgwardt
FieldData Mining
Address
Dep. Biosysteme
ETH Zürich, D-BSSE, BSD G 234
Mattenstrasse 26
4058 Basel
SWITZERLAND
Award: The Golden Owl
Telephone+41 61 387 34 20
E-mailkarsten.borgwardt@bsse.ethz.ch
URLhttps://bsse.ethz.ch/mlcb
DepartmentBiosystems Science and Engineering
RelationshipFull Professor

NumberTitleECTSHoursLecturers
636-0018-00LData Mining I6 credits3G + 2AK. M. Borgwardt
AbstractData 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.
ObjectiveThe 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.
ContentThe 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
2. Classification
3. Clustering
4. Feature Selection
Lecture notesCourse material will be provided in form of slides.
LiteratureWill be provided during the course.
Prerequisites / NoticeBasic understanding of mathematics, as taught in basic mathematics courses at the Bachelor's level.
636-0301-00LCurrent Topics in Biosystems Science and Engineering
For doctoral students only.
Master's students cannot receive credits for the seminar.
2 credits1SR. 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
AbstractThis seminar will feature invited lectures about recent advances and developments in systems biology, including topics from biology, bioengineering, and computational biology.
ObjectiveTo provide an overview of current systems biology research.
ContentThe final list of topics will be available at https://www.bsse.ethz.ch/news-and-events/seminar-series.html