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Bioinformatics approaches for unveiling virus-host interactions
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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969756/ https://www.ncbi.nlm.nih.gov/pubmed/36874163 http://dx.doi.org/10.1016/j.csbj.2023.02.044 |
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author | Iuchi, Hitoshi Kawasaki, Junna Kubo, Kento Fukunaga, Tsukasa Hokao, Koki Yokoyama, Gentaro Ichinose, Akiko Suga, Kanta Hamada, Michiaki |
author_facet | Iuchi, Hitoshi Kawasaki, Junna Kubo, Kento Fukunaga, Tsukasa Hokao, Koki Yokoyama, Gentaro Ichinose, Akiko Suga, Kanta Hamada, Michiaki |
author_sort | Iuchi, Hitoshi |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9969756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-99697562023-02-27 Bioinformatics approaches for unveiling virus-host interactions Iuchi, Hitoshi Kawasaki, Junna Kubo, Kento Fukunaga, Tsukasa Hokao, Koki Yokoyama, Gentaro Ichinose, Akiko Suga, Kanta Hamada, Michiaki Comput Struct Biotechnol J Review Article 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. Research Network of Computational and Structural Biotechnology 2023-02-27 /pmc/articles/PMC9969756/ /pubmed/36874163 http://dx.doi.org/10.1016/j.csbj.2023.02.044 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Review Article Iuchi, Hitoshi Kawasaki, Junna Kubo, Kento Fukunaga, Tsukasa Hokao, Koki Yokoyama, Gentaro Ichinose, Akiko Suga, Kanta Hamada, Michiaki Bioinformatics approaches for unveiling virus-host interactions |
title | Bioinformatics approaches for unveiling virus-host interactions |
title_full | Bioinformatics approaches for unveiling virus-host interactions |
title_fullStr | Bioinformatics approaches for unveiling virus-host interactions |
title_full_unstemmed | Bioinformatics approaches for unveiling virus-host interactions |
title_short | Bioinformatics approaches for unveiling virus-host interactions |
title_sort | bioinformatics approaches for unveiling virus-host interactions |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9969756/ https://www.ncbi.nlm.nih.gov/pubmed/36874163 http://dx.doi.org/10.1016/j.csbj.2023.02.044 |
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