Defining the protein interaction network of human malaria parasite Plasmodium falciparum
Type
ArticleKAUST Department
Applied Mathematics and Computational Science ProgramBiological and Environmental Sciences and Engineering (BESE) Division
Bioscience Program
Computational Bioscience Research Center (CBRC)
Date
2012-02Permanent link to this record
http://hdl.handle.net/10754/565967
Metadata
Show full item recordAbstract
Malaria, caused by the protozoan parasite Plasmodium falciparum, affects around 225. million people yearly and a huge international effort is directed towards combating this grave threat to world health and economic development. Considerable advances have been made in malaria research triggered by the sequencing of its genome in 2002, followed by several high-throughput studies defining the malaria transcriptome and proteome. A protein-protein interaction (PPI) network seeks to trace the dynamic interactions between proteins, thereby elucidating their local and global functional relationships. Experimentally derived PPI network from high-throughput methods such as yeast two hybrid (Y2H) screens are inherently noisy, but combining these independent datasets by computational methods tends to give a greater accuracy and coverage. This review aims to discuss the computational approaches used till date to construct a malaria protein interaction network and to catalog the functional predictions and biological inferences made from analysis of the PPI network. © 2011 Elsevier Inc.Sponsors
This work was funded by King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia.Publisher
Elsevier BVJournal
GenomicsPubMed ID
22178265ae974a485f413a2113503eed53cd6c53
10.1016/j.ygeno.2011.11.006
Scopus Count
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