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2000
Volume 26, Issue 26
  • ISSN: 1381-6128
  • E-ISSN: 1873-4286

Abstract

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.

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/content/journals/cpd/10.2174/1381612826666200310122324
2020-07-01
2025-09-13
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/content/journals/cpd/10.2174/1381612826666200310122324
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  • Article Type:
    Review Article
Keyword(s): database; feature; infection; machine learning; malaria parasite; Mitochondria proteins
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