Deep learning based on biologically interpretable genome representation predicts two types of human adaptation of SARS-CoV-2 variants. - Jing Li 121; Ya-Nan Wu; Sen Zhang; Xiao-Ping Kang; Tao Jiang 043 (Briefings Bioinform., 2022)

Genome-based intelligent prediction of the reassortment potential between H5N1 and H3N2 influenza viruses. - Jing Li 121 (Zenodo, 2024)

SCoV2-VAR: A light-weighted, customizable, and open-source database of 12 million SARS-CoV-2 genomes. - Jing Li 121 (Zenodo, 2024)

ARNLE model identifies prevalence potential of SARS-CoV-2 variants. - Yuqi Liu; Jing Li 121; Peihan Li; Yehong Yang; Kaiying Wang; Jinhui Li; Lang Yang; Jiangfeng Liu; Leili Jia; Aiping Wu; Juntao Yang; Peng Li 041; et al. (Nat. Mac. Intell., 2025)

SCoV2-VAR: A light-weighted, customizable, and open-source database of 12 million SARS-CoV-2 genomes. - Jing Li 121 (Zenodo, 2025)