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| Session Chair, Stefan Kramer, Technische Universitaet Muenchen |
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Prof. Dr. Stefan Kramer is head of the Machine Learning and Data Mining in Bioinformatics Group at Technische Universitaet Muenchen. His research interests are in Bioinformatics, Chemoinformatics, Predictive Toxicology, Machine Learning, Data Mining, Relational Data Mining, Inductive Logic Programming, Inductive Databases, and Software Engineering. He is the Program Chair of the Fifteenth International Conference on Inductive Logic Programming (ILP-2005), was a Co-Editor of a special issue of the Machine Learning journal on Multi-Relational Data Mining and Statistical Relational Learning, and a Co-Editor of a special section in Bioinformatics on the Predictive Toxicology Challenge 2000-2001.
The focus of his research group is the integration of machine learning and data mining features into bioinformatics databases and the integration of heterogeneous data in bioinformatics. A key concept of the proposed solution is that of an 'inductive database', that is, a database that cannot only be queried over the data residing in it, but also over the patterns and models that are valid in the data. Inductive databases have a great potential for the field of bioinformatics, since they support scientists in the interactive exploration of experimental and other (e.g., text) data. Regarding the representation of data and knowledge, the emphasis of his research is on machine learning and data mining in logic-based and graph-based formalisms. From the biological perspective, the group works on predictive toxicology and toxicogenomics.
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