文献类型：期刊文献

英文题名：Variation and evolution analysis of SARS-CoV-2 using self-game sequence optimization

作者：Liu, Ziyu[1];Shen, Yi[2];Jiang, Yunliang[3];Zhu, Hancan[4];Hu, Hailong[1];Kang, Yanlei[1];Chen, Ming[2];Li, Zhong[1]

机构：[1]Huzhou Univ, Sch Informat Engn, Huzhou, Zhejiang, Peoples R China;[2]Zhejiang Univ, Coll Life Sci, Hangzhou, Zhejiang, Peoples R China;[3]Zhejiang Normal Univ, Sch Comp Sci & Technol, Jinhua, Zhejiang, Peoples R China;[4]Shaoxing Univ, Sch Math Phys & Informat, Shaoxing, Zhejiang, Peoples R China

年份：2024

卷号：15

外文期刊名：FRONTIERS IN MICROBIOLOGY

收录：SCI-EXPANDED(收录号：WOS:001362030100001)、、Scopus(收录号：2-s2.0-85210593679)、WOS

基金：We would like to thank BioRender.com, which agrees us and provides some resources for the completion of Figure 1 in this article.

语种：英文

外文关键词：deep learning; SARS-CoV-2; evolution analysis; self-game sequence optimization; DARSEP model

外文摘要：Introduction The evolution of SARS-CoV-2 has precipitated the emergence of new mutant strains, some exhibiting enhanced transmissibility and immune evasion capabilities, thus escalating the infection risk and diminishing vaccine efficacy. Given the continuous impact of SARS-CoV-2 mutations on global public health, the economy, and society, a profound comprehension of potential variations is crucial to effectively mitigate the impact of viral evolution. Yet, this task still faces considerable challenges.Methods This study introduces DARSEP, a method based on Deep learning Associates with Reinforcement learning for SARS-CoV-2 Evolution Prediction, combined with self-game sequence optimization and RetNet-based model.Results DARSEP accurately predicts evolutionary sequences and investigates the virus's evolutionary trajectory. It filters spike protein sequences with optimal fitness values from an extensive mutation space, selectively identifies those with a higher likelihood of evading immune detection, and devises a superior evolutionary analysis model for SARS-CoV-2 spike protein sequences. Comprehensive downstream task evaluations corroborate the model's efficacy in predicting potential mutation sites, elucidating SARS-CoV-2's evolutionary direction, and analyzing the development trends of Omicron variant strains through semantic changes.Conclusion Overall, DARSEP enriches our understanding of the dynamic evolution of SARS-CoV-2 and provides robust support for addressing present and future epidemic challenges.