Defining the protein interaction network of human malaria parasite Plasmodium falciparum

Abhinay Ramaprasad, Arnab Pain, Timothy Ravasi

Research output: Contribution to journalArticlepeer-review

24 Scopus citations

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. © 2011 Elsevier Inc.
Original languageEnglish (US)
Pages (from-to)69-75
Number of pages7
JournalGenomics
Volume99
Issue number2
DOIs
StatePublished - Feb 2012

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was funded by King Abdullah University of Science and Technology, Thuwal, Kingdom of Saudi Arabia.

ASJC Scopus subject areas

  • Genetics

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