Sofia Tapanelli

The paper uses machine learning to predict essential genes across eukaryotes, achieving high accuracy and validating predictions in Tribolium castaneum.

This paper converts endogenous mosquito genes into non-autonomous gene drives for malaria control by using native regulatory sequences to express antimalarial molecules and guide-RNAs.

This study identifies PIMMS43 as a key parasite protein enabling evasion of the mosquito complement-like response and sporogonic development, suggesting it as a target for malaria transmission-blocking interventions.