Learning From Biological Data: Methods and Applications

PhD defence, Wednesday 23 May 2018, Dan Søndergaard.

2018.05.23 | Trine Berndt Turtiainen Scheelke

Dan Søndergaard

During his studies, Dan Søndergaard has researched the application of machine learning to biological data, with a focus on simple, interpretable models. While models such as neural networks have become extremely popular for many applications, such models are not always ideal for problems in biology. Dan Søndergaard applied simple methods such as the k-nearest neighbour method to a variety of protein sequence classification problems and shows that this simple method often outperforms much more complex methods. However, for some problems, such as predicting the cancer in cases of cancer of unknown primary, more complex methods are needed. Dan Søndergaard presents such a method which attempts to improve predictions by taking tumour sample impurities into account.

The PhD degree was completed at the Bioinformatics Research Centre, Science and Technology, Aarhus University.

This résumé was prepared by the PhD student.

Time: Wednesday May 23 2018 at 15.15
Place: Building 1110, room 223, Bioinformatics Research Centre, C.F. Møllers Allé 8, Aarhus University, 800 Aarhus C.
Title of PhD thesis: Classification and analysis of biological data
Contact information: Dan Søndergaard, e-mail: das@birc.au.dk, tel.: +45 22 66 68 77
Members of the assessment committee:
Professor Jan Baumbach, School of Life Sciences, Technical University of Munich
Associate Professor Richard Röttger, Dept. of Mathematics and Computer Science (IMADA), University of Southern Denmark
Associate Professor Asger Hobolth, Bioinformatics Research Centre, Aarhus University (chair)
Main supervisor:
Associate Professor Christian Nørgaard Storm Pedersen, Bioinformatics Research Centre, Aarhus University
Language: The PhD thesis will be defended in English


The defence is public.
The dissertation is available for reading at the Graduate School of Science and Technology/GSST,
Ny Munkegade 120, building 1520, rooms 128-134, 8000 Aarhus C.

PhD defence
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Revised 16.04.2018