Bioinformatics approaches for unveiling virus-host interactions

Hitoshi Iuchi*, Junna Kawasaki, Kento Kubo, Tsukasa Fukunaga, Koki Hokao, Gentaro Yokoyama, Akiko Ichinose, Kanta Suga, Michiaki Hamada

*この研究の対応する著者

研究成果: Review article査読

抄録

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.

本文言語English
ページ(範囲)1774-1784
ページ数11
ジャーナルComputational and Structural Biotechnology Journal
21
DOI
出版ステータスPublished - 2023 1月

ASJC Scopus subject areas

  • バイオテクノロジー
  • 生物理学
  • 構造生物学
  • 生化学
  • 遺伝学
  • コンピュータ サイエンスの応用

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