Int. J. of Computational Biology and Drug Design   »   2017 Vol.10, No.2

 

 

Title: PageRank influence analysis of protein-protein association networks in the malaria parasite Plasmodium falciparum

 

Authors: Xinran Yu; Timothy G. Lilburn; Hong Cai; Jianying Gu; Turgay Korkmaz; Yufeng Wang

 

Addresses:
Department of Computer Science, University of Texas at San Antonio, San Antonio, TX 78249, USA
Novozymes NA Inc., Durham, NC 27709, USA
Department of Biology, South Texas Center for Emerging Infectious Diseases, University of Texas at San Antonio, San Antonio, TX 78249, USA
Department of Biology, College of Staten Island, City University of New York, Staten Island, NY 10314, USA
Department of Computer Science University of Texas at San Antonio San Antonio, TX 78249, USA
Department of Biology, South Texas Center for Emerging Infectious Diseases, University of Texas at San Antonio, San Antonio, TX 78249, USA

 

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.

 

Keywords: malaria; plasmodium; PageRank; systems biology; network.

 

DOI: 10.1504/IJCBDD.2017.10004576

 

Int. J. of Computational Biology and Drug Design, 2017 Vol.10, No.2, pp.137 - 156

 

Submission date: 30 Jul 2016
Date of acceptance: 19 Sep 2016
Available online: 15 Apr 2017

 

 

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