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In recent years, several computational methods have been developed to predict protein-protein interactions (PPIs) at a genome-wide level. Between them phylogenetic profiling is routinely used to infer PPIs occurring within an organism. Recent improvements of the methods rely on the usage of large genomic datasets and on the distance correlation, a correlation-based measure, as novel measure of profile similarity. Here we adapted the robust improved phylogenetic profiling strategy to predict PPIs occurring between organisms. Specifically, we inferred PPIs occurring in the host-parasite system of Plasmodium falciparum, the deadliest human malaria parasite, and the human erythrocyte, in which the parasite performs an asexual reproduction and that is responsible of the greatest part of the parasitosis symptoms. By applying the method we could predict host-host, erythrocyte-erythrocyte and host-erythrocyte PPIs. As proof of principle, we demonstrated that the phylogenetic profiling can be extended to predict interactions that not necessarily are performed by proteins belonging to the same organism.
“This is an abstract which has been accepted for the BBCC2018 Conference