Developing Machine Learning Approaches for the Effect of Rare Genetic Variants on Protein Function and Disease
As genomic data grows rapidly, there's a need for advanced methods to process it for medical insights. In Dr. Henrike Heyne's lab I'm working on the development of machine learning approaches to understand how rare genetic changes impact protein function and contribute to human diseases like epilepsy. This research aims to enhance our understanding of the link between genetics and health, potentially improving diagnostics and treatment strategies.
Poster presentation at RECOMB 2023: Rissom, Pia F. and Miranda, Fabio M., and Renard, Bernhard Y. and Baum, Katharina. „A Machine Learning Pipeline Enabling Network-based Tissue-specific Protein Function Prediction”.
