Stefan Born | Lecturer
Technische Universität Berlin

Stefan Born, Lecturer, Technische Universität Berlin

Stefan Born studied Mathematics and Physics in Heidelberg, Paris VI and Gießen and is presently a lecturer at TU Berlin. After collaborations on machine learning and data modelling tasks with the Information Systems Machine Learning Lab (ISMLL) in Hildesheim und the Institute for Biochemistry in Greifswald, he headed (2020-2023) the Machine Learning "task force" in the federally funded project  "KIWI-biolab"  at TU Berlin, where he worked on flexible and robust ML methods for fully automated experimental loops in bioprocess development  and, in a subproject with Greifswald, for the semi-rational design of new enzyme variants. He works with Mark Dörr (Greifswald) on the development of generic (predictive) modelling tools for protein properties with a focus on transfer learning, and the integration of such tools into experimental workflows.

Appearances:



Day 1 (26th June) @ 16:00

Full integration of ML into an ontology guided automated robotic workflow

LARA is an open source and free research data management system, which aims at fully automatise the process of experimentation, data acquisition, semantic annotation, search and synchronisation with other laboratories. The use case of machine learning guided protein engineering with the Protein Prediction Utils (PPU) shall be demonstrated. PPU is an open python package meant to provide a generic way for defining predictive models for protein properties (enzyme activity on specific substrates, solubility, etc.). Models specify data aggregation, preprocessing, training and validation using the terms defined in ontologies underlying the data management of LARA, thus ensuring the automatic interoperability.

last published: 14/Jun/24 11:25 GMT

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