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Bioinformatics approaches for unveiling virus-host interactions

Authors :
Hitoshi Iuchi
Junna Kawasaki
Kento Kubo
Tsukasa Fukunaga
Koki Hokao
Gentaro Yokoyama
Akiko Ichinose
Kanta Suga
Michiaki Hamada
Source :
Computational and Structural Biotechnology Journal, Vol 21, Iss , Pp 1774-1784 (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

The coronavirus disease-2019 (COVID-19) pandemic has elucidated major limitations in the capacity of medical and research institutions to appropriately manage emerging infectious diseases. We can improve our understanding of infectious diseases by unveiling virus–host interactions through host range prediction and protein–protein interaction prediction. Although many algorithms have been developed to predict virus–host interactions, numerous issues remain to be solved, and the entire network remains veiled. In this review, we comprehensively surveyed algorithms used to predict virus–host interactions. We also discuss the current challenges, such as dataset biases toward highly pathogenic viruses, and the potential solutions. The complete prediction of virus–host interactions remains difficult; however, bioinformatics can contribute to progress in research on infectious diseases and human health.

Details

Language :
English
ISSN :
20010370 and 04522931
Volume :
21
Issue :
1774-1784
Database :
Directory of Open Access Journals
Journal :
Computational and Structural Biotechnology Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.560aeede5c04522931a8e442fdbc0dd
Document Type :
article
Full Text :
https://doi.org/10.1016/j.csbj.2023.02.044