Panagiotis Nikolaos Lalagkas

This paper disentangles disease genes contributing to drug therapeutic benefits versus side effects using a network model and identifies insights for drug repurposing and treatment selection.

This paper uses genetic similarity between diseases to predict drug therapeutic and side effects, finding higher genetic similarity correlates with shared drug outcomes.

The paper identifies novel breast cancer treatment candidates by leveraging shared genetic associations between breast cancer and its predisposing diseases.

The paper uses Mendelian disease comorbidity to identify potential drug targets for complex diseases by linking causal genes and their associated drugs.

This paper develops Draphnet, a model that connects drug molecular effects to disease genetics to predict and explain drug impacts on disease phenotypes.