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

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

Abstract 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...

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Bibliographic Details
Main Authors: Lun Hu, Zhenfeng Li, Zehai Tang, Cheng Zhao, Xi Zhou, Pengwei Hu
Format: Article
Language:English
Published: BMC 2022-10-01
Series:BMC Bioinformatics
Subjects:
HIV-1 protease
Cleavage sites prediction
Asymmetric bagging
Biased SVM
Ensemble learning
Online Access:https://doi.org/10.1186/s12859-022-04999-y

Internet

https://doi.org/10.1186/s12859-022-04999-y

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