Transcriptomics machine learning models
Development of hybrid transcriptomics machine learning models for drug discovery. In order to approach a holistic transcriptome model, both unsupervised and supervised learning are applied to integrate transcriptomics data. This project is part of the AI & Data Science Fellowship Program (https://uni-tuebingen.de/en/237054) – a collaboration between Tübingen University and Boehringer Ingelheim – aiming to develop cutting-edge machine learning models with implications for pharmaceutical research.
