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Journal of Molecular Evolution|July 11, 2026
Classification of SARS-CoV-2 Variants Through the Epistatic Circos Plots with Convolutional Neural NetworksBo Jing, Kai-Rui Zhang, Hong-Li Zeng, et al.Physical Biology|November 13, 2024
Two fitness inference schemes compared using allele frequencies from 1068 391 sequences sampled in the UK during the COVID-19 pandemicHong-Li Zeng, Cheng-Long Yang, Bo Jing, et al.Physical Review. E|June 25, 2020
Inferring genetic fitness from genomic dataHong-Li Zeng, Erik AurellReports on Progress in Physics. Physical Society (Great Britain)|March 21, 2023
Statistical genetics in and out of quasi-linkage equilibriumVito Dichio, Hong-Li Zeng, Erik AurellPhysical Review. E, Statistical, Nonlinear, and Soft Matter Physics|May 24, 2011
Network inference using asynchronously updated kinetic Ising modelHong-Li Zeng, Erik Aurell, Mikko Alava, et al.Physical Review. E|November 18, 2022
Temporal epistasis inference from more than 3 500 000 SARS-CoV-2 genomic sequencesHong-Li Zeng, Yue Liu, Vito Dichio, et al.Arxiv|November 24, 2025
Fitness inference tested by in silico population geneticsHong-Li Zeng, Yu-Han Huang, John Barton, et al.Physical Review. E|May 16, 2026
Fitness inference tested by in silico population geneticsHong-Li Zeng, Yu-Han Huang, Erik Aurell, et al.Physical Review Letters|June 11, 2013
Maximum likelihood reconstruction for Ising models with asynchronous updatesHong-Li Zeng, Mikko Alava, Erik Aurell, et al.Proceedings of the National Academy of Sciences of the United States of America|November 18, 2020
Global analysis of more than 50,000 SARS-CoV-2 genomes reveals epistasis between eight viral genesHong-Li Zeng, Vito Dichio, Edwin Rodríguez Horta, et al.Pageof 42