We are seeking a highly motivated postdoctoral researcher with a strong computational background to join our research project on protein-protein interaction (PPI) networks. Our work addresses critical challenges in network biology. This project has a focus on enhancing the reliability and interpretability of protein-protein interaction data. You will be joining a vibrant international team at one of Europe’s leading cancer research institutes.
Protein-protein interaction networks are key to understanding biological and disease processes, but current methods to detect, integrate and analyze those networks suffer from high technical error rates and biases, especially toward frequently studied proteins. In a joint project with the Friedrich Alexander University (Erlangen, Germany) and the Technical University of Munich (Germany), we aim to improve the quality of PPI networks by leveraging large scale experimental information towards two key objectives:
Developing a negative gold standard for PPI prediction: We will create a robust set of pairs of proteins that are highly unlikely to interact, providing essential negative examples for machine learning models.
Mitigating the study bias in PPI networks: We will design and implement algorithms to reduce the impact of false positives caused by the over-testing of certain proteins, ultimately improving the accuracy and reliability of PPI networks.