Inferring the skeleton cell cycle regulatory network of malaria parasite using comparative genomic and variational Bayesian approaches

The development of new antimalarial drugs is urgently needed due to elevated drug resistance in the causative agents Plasmodium parasites. An intervention strategy based on the interruption of the parasite cell cycle could be undertaken using a systems-biology aided drug discovery approach. However, little is known about the components or the mechanism of parasite cell cycle control to date. In this proof of concept study, we attempted to infer the skeleton components using comparative genomic analysis and to uncover the genetic regulatory network (GRN) ab initio using a Variational Bayesian expectation maximization (VBEM) approach.