Effectively predicting HIV-1 protease cleavage sites by using an ensemble learning approach

BACKGROUND: The site information of substrates that can be cleaved by human immunodeficiency virus 1 proteases (HIV-1 PRs) is of great significance for designing effective inhibitors against HIV-1 viruses. A variety of machine learning-based algorithms have been developed to predict HIV-1 PR cleavag...

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Detalles Bibliográficos
Autores principales: Hu, Lun, Li, Zhenfeng, Tang, Zehai, Zhao, Cheng, Zhou, Xi, Hu, Pengwei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9608884/
https://www.ncbi.nlm.nih.gov/pubmed/36303135
http://dx.doi.org/10.1186/s12859-022-04999-y

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9608884/
https://www.ncbi.nlm.nih.gov/pubmed/36303135
http://dx.doi.org/10.1186/s12859-022-04999-y

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