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Similarity Measures and Machine Learning in In Silico-Toxicology
Machine-learning models for toxicology predictions are a promising tool in the process of reducing, refining and replacing animal testing. My thesis focuses on the design of novel fingerprints and the investigation of appropriate similarity measures and thresholds. In a collaboration with BASF Ludwigshafen we work on the application of computer models for read-across.