The number of human deaths caused by malaria is increasing day-by-day. In fact, the mitochondrial
proteins of the malaria parasite play vital roles in the organism. For developing effective drugs and vaccines
against infection, it is necessary to accurately identify mitochondrial proteins of the malaria parasite. Although
precise details for the mitochondrial proteins can be provided by biochemical experiments, they are expensive and
time-consuming. In this review, we summarized the machine learning-based methods for mitochondrial proteins
identification in the malaria parasite and compared the construction strategies of these computational methods.
Finally, we also discussed the future development of mitochondrial proteins recognition with algorithms.