Predicting antigenic variants of H1N1 influenza virus based on epidemics and pandemics using a stacking model

• Main Authors: Yin, Rui, Tran, Viet Hung, Zhou, Xinrui, Zheng, Jie, Kwoh, Chee Keong
• Other Authors: School of Computer Science and Engineering
• Format: Article
• Language: English
• Published: 2022
• Subjects: Engineering::Computer science and engineering; Influenza H1N1; Antigenic Variant; Pandemics; Epidemics; Stacking Model
• Online Access: https://hdl.handle.net/10356/155627
• Institution: Nanyang Technological University

H1N1 is the earliest emerging subtype of influenza A viruses with available genomic sequences, has caused several pandemics and seasonal epidemics, resulting in millions of deaths and enormous economic losses. Timely determination of new antigenic variants is crucial for the vaccine selection and fl...