PageRank influence analysis of protein-protein association networks in the malaria parasite Plasmodium falciparum
by Xinran Yu; Timothy G. Lilburn; Hong Cai; Jianying Gu; Turgay Korkmaz; Yufeng Wang
International Journal of Computational Biology and Drug Design (IJCBDD), Vol. 10, No. 2, 2017

Abstract: Malaria has caused millions of deaths over the years and it is still a major scourge in its endemic regions. Resistance to even the most recently developed effective treatments has emerged. A deeper understanding of parasite biology and host-parasite interactions will enable new, robust measures against the malaria parasite. In this paper, we developed a novel PageRank-based network analysis approach to identify proteins that are potentially influential in protein-protein association networks in Plasmodium falciparum. The proteins that were predicted to be most influential are involved in transcriptional regulation, signalling, proteolysis, and heat shock response. They are associated with proteins that may play a role in fundamental processes that range from genetic information processing, metabolism, transport, development, to virulence to the host. Functional characterisation of these proteins may open venues for novel therapeutics for effective malaria eradication.

Online publication date: Tue, 25-Apr-2017

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