Literature DB >> 32156226

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

Ting Liu1, Hua Tang1.   

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. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

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Keywords:  Mitochondria proteins; database; feature; infection; machine learning; malaria parasite

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Year:  2020        PMID: 32156226     DOI: 10.2174/1381612826666200310122324

Source DB:  PubMed          Journal:  Curr Pharm Des        ISSN: 1381-6128            Impact factor:   3.116


  1 in total

1.  Barnacles Mating Optimizer with Deep Transfer Learning Enabled Biomedical Malaria Parasite Detection and Classification.

Authors:  Ashit Kumar Dutta; R Uma Mageswari; A Gayathri; J Mary Dallfin Bruxella; Mohamad Khairi Ishak; Samih M Mostafa; Habib Hamam
Journal:  Comput Intell Neurosci       Date:  2022-06-01
  1 in total

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