Title
PageRank influence analysis of protein-protein association networks in the malaria parasite Plasmodium falciparum.
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.
Year
Venue
Field
2017
I. J. Computational Biology and Drug Design
PageRank,Transcriptional regulation,Biology,Heat shock,Systems biology,Plasmodium falciparum,Malaria,Bioinformatics,Parasite hosting,Virulence
DocType
Volume
Issue
Journal
10
2
Citations 
PageRank 
References 
1
0.35
0
Authors
6
Name
Order
Citations
PageRank
Xinran Yu132.53
Timothy Lilburn211.02
Hong Cai36511.01
Jianying Gu4206.05
Turgay Korkmaz582759.69
Yufeng Wang65114.37