Florin Ratajczak

The paper shows that sampling biases in negative regulatory interactions inflate performance in gene regulatory network inference and proposes a degree-aware sampling approach to address this issue.

The paper investigates the role of mitochondrial DNA in gene regulation across 48 tissues and 684 individuals, identifying eQTLs and associations with nuclear DNA genes.

Speos predicts core genes for complex diseases using graph representation learning, achieving validation rates comparable to Mendelian disorder genes and identifying druggable targets.