A Brief Survey of Machine Learning Methods in Identification of Mitochondria Proteins in Malaria Parasite

被引:2
|
作者
Liu, Ting [1 ]
Tang, Hua [1 ]
机构
[1] Southwest Med Univ, Dept Pathophysiol, Key Lab Med Electrophysiol, Minist Educ, Luzhou 646000, Peoples R China
关键词
Mitochondria proteins; malaria parasite; machine learning; database; feature; infection; AMINO-ACID-COMPOSITION; SUPPORT VECTOR MACHINE; FEATURE-SELECTION; SUBCELLULAR-LOCALIZATION; ANTIGENIC DETERMINANTS; MYCOBACTERIAL PROTEINS; STRUCTURAL CLASSES; BINDING-SITES; WEB SERVER; CD-HIT;
D O I
10.2174/1381612826666200310122324
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
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.
引用
收藏
页码:3049 / 3058
页数:10
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