Recognition of Mitochondrial Proteins in Plasmodium Based on the Tripeptide Composition - Bian, Haodong; Guo, Maozu; Wang, Juan (Frontiers in Cell and Developmental Biology, 2020)
Mitochondria play essential roles in eukaryotic cells, especially in Plasmodium cells. They have some unusual evolutionary and functional features that are incredibly vital for disease diagnosis and drug design. Thus, predicting mitochondrial proteins of Plasmodium has become a worthwhile work. However, existing computational methods can only predict mitochondrial proteins of Plasmodium falciparum, and these methods have low accuracy. It is highly desirable to design a classifier with high accuracy for predicting mitochondrial proteins for all Plasmodium species, not only Plasmodium falciparum. We proposed a novel method, named as PM-OTC, for predicting mitochondrial proteins in Plasmodium. PM-OTC uses the support vector machine as the classifier and the selected tripeptide composition as the features. We adopted the 5-fold cross-validation method to train and test PM-OTC. Results demonstrate that PM-OTC achieves an accuracy of 94.91%, and PM-OTC performances are superior to other methods.