Research

Thesis title: "Biological and Chemical Fingerprinting for Target Prediction"

Thesis outline: Palle Helmke's work focuses on the establishment of KNIME workflows to enrich compound-target interaction fingerprints with visualisation in heatmaps. This will be further implemented on steatosis as main use case. In addition, this aim will be accomplished by creating machine learning models for classification using compound-target interaction fingerprints for instance.

Supervisor & Co-Mentor: Gerhard Ecker, Daniela Digles

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