Teaching

Summer 2017: Genome Maps & Genome-Wide Association Studies

Introductory lecture about different types of maps for genetic and genomic data, as well as methods on how to create a physical map.

 

Slides can be found here (German only): Algorithmen und Anwendungen zur Kartierung von Genomen

 

  • Jupiter Notebook about Double Digest to create a physical map (German only)

 

The second talk is about foundations of Genome-Wide Association Studies, current challenges and future perspectives.

 

Summer 2017: Ridge Regression, Support Vector Machines & Feature Selection

Introductory lecture about Ridge Regression and Support Vector Machines. The lecture gives a brief introduction what is regression and how Ridge Regression can help to avoid overfitting and underfitting. The second part of the lecture is about classification with Support Vector Machines. Here, we will introduce the concept of Hard-Margin SVM and Soft-Margin SVM. Further, we will give a brief introduction into Kernel functions and how they can be used in a SVM to solve non-linear separable discrimination problems.

Slides can be found here (German only):

„Ridge Regression“ und „Kernalized Support Vector Machines“: Eine Einführung an einem Anwendungsbeispiel

Jupyter Notebooks with different examples about the covered topics can be found at GitHub for download or here:

The second lecture is a brief introduction into Feature Selection for high-dimensional data using regularisation. Further, the lecture contains a small primer on how to integrate prior-knowledge.

Slides can be found here: A Primer on Feature Selection for High-Dimensional Data

Summer 2016: Data Mining II 

Data Mining II course. I was given the practical sessions of this course including Python programming sessions. Topics have been different types of dimensionality reduction methods, such as SVD, PCA, MDS or LDA.
The course website can be found here.

Winter 2015-16: Genomic Medicine

P.hD. block course organised by Prof. Dr. Niko Beerenwinkel and Dr. Daniel Stekhoven at ETH Zürich.
The course website can be found here.
My lecture slides for „GWASs in Medicine“ can be downloaded here: PDF
Tutorials for this lecture can be downloaded here: PDF

Winter 2015-16: Data Mining I

Data Mining I course. I was given the practical sessions of this course including Python programming sessions. Topics included, distance metrics, classification, clustering, feature selection, model evaluation, and applications of machine learning in computational biology.
The course website can be found here.

Summer 2013: Seminar Bioinformatics I

Bioinformatics Seminar taught at the University of Tübingen. I was helping as tutor.

Winter 2012-13: Data Mining in Bioinformatics

Course (M.Sc. level) taught with Karsten Borgwardt and Chloé-Agathe Azencott at the University of Tübingen.
The course website can be found here.
My lecture slides for „Day 6: Classification in Next Generation Sequencing Data Analysis“ can be downloaded here: PDF

Summer 2012: Seminar Bioinformatics I

Bioinformatics Seminar taught at the University of Tübingen. I was helping as tutor.

Winter 2011-12: Data Mining in Bioinformatics

Data Mining in Bioinformatics taught at the University of Tübingen. I was helping as tutor.