Division of Chemical & Life Sciences and Engineering, King Abdullah University of Science and Technology Thuwal 23955, Saudi Arabia.
Genomics. 2012 Feb;99(2):69-75. doi: 10.1016/j.ygeno.2011.11.006. Epub 2011 Dec 8.
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.
疟疾是由疟原虫寄生虫引起的，每年影响约 2.25 亿人，国际社会为此做出了巨大努力，以应对这一对世界健康和经济发展的严重威胁。2002 年疟疾基因组测序引发了疟疾研究的重大进展，随后进行了多项高通量研究，定义了疟疾转录组和蛋白质组。蛋白质-蛋白质相互作用（PPI）网络试图追踪蛋白质之间的动态相互作用，从而阐明它们的局部和全局功能关系。通过酵母双杂交（Y2H）筛选等高通量方法获得的实验衍生的 PPI 网络本质上存在噪声，但通过计算方法组合这些独立数据集往往可以提高准确性和覆盖范围。这篇综述旨在讨论迄今为止用于构建疟疾蛋白质相互作用网络的计算方法，并列出从 PPI 网络分析中得出的功能预测和生物学推论。
