title: Defining the protein interaction network of human malaria parasite Plasmodium falciparum.
abstract: 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.
authors.affiliation: Division of Chemical & Life Sciences and Engineering, King Abdullah University of Science and Technology Thuwal 23955, Saudi Arabia.
authors.forename: Abhinay
authors.initials: A
authors.lastname: Ramaprasad
authors.forename: Arnab
authors.initials: A
authors.lastname: Pain
authors.forename: Timothy
authors.initials: T
authors.lastname: Ravasi
mesh_terms: D000818:Animals; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D010963:Plasmodium falciparum / Q000378:metabolism*; D025941:Protein Interaction Mapping; D060066:Protein Interaction Maps; D020543:Proteome / Q000378:metabolism; D015800:Protozoan Proteins / Q000378:metabolism
chemical_list: D020543:Proteome; D015800:Protozoan Proteins