Prediction of novel systems components in cell cycle regulation in malaria parasite by subnetwork alignments

Abstract

With 300-500 clinical cases and 1-2 million deaths yearly, malaria contributes to enormous health care and economic burden worldwide. The advent of high throughput -omics technologies is driving new approaches to the identification of potential antimalarial targets. In this paper, we propose a neighborhood subnetwork alignment approach to uncover the network components involved in cell cycle regulation of the malaria parasite Plasmodium falciparum and to assign function to previously unannotated proteins.