activity
20212026
collaborators

5 papers

q-bio.PE2026

Fitness Inference in Presence of Migrations between Coupled Evolving Populations

Yu-Han Huang, Bastien Dumont, Hong-Li Zeng +2

The phase of Quasi-Linkage Equilibrium (QLE) in evolutionary populations is analogous to the thermal equilibrium state in statistical mechanics, a concept pioneered by Kimura in 19…

q-bio.GN2026

Classification of SARS-CoV-2 Variants through The Epistatical Circos Plots with Convolutional Neural Networks

Bo Jing, Kai-Rui Zhang, Hong-Li Zeng +1

The COVID-19 pandemic has profoundly affected global health, driven by the remarkable transmissibility and mutational adaptability of the SARS-CoV-2 virus. Although five variants o…

q-bio.PE2025

Fitness inference tested by in silico population genetics

Hong-Li Zeng, Yu-Han Huang, John Barton +1

We consider populations evolving according to natural selection, mutation, and recombination, and assume that the genomes of all or a representative selection of individuals are kn…

q-bio.PE2024

Two fitness inference schemes compared using allele frequencies from 1,068,391 sequences sampled in the UK during the COVID-19 pandemic

Hong-Li Zeng, Cheng-Long Yang, Bo Jing +2

Throughout the course of the SARS-CoV-2 pandemic, genetic variation has contributed to the spread and persistence of the virus. For example, various mutations have allowed SARS-CoV…

q-bio.PE2021

Mutation frequency time series reveal complex mixtures of clones in the world-wide SARS-CoV-2 viral population

Hong-Li Zeng, Yue Liu, Vito Dichio +3

We compute the allele frequencies of the alpha (B.1.1.7), beta (B.1.351) and delta (B.167.2) variants of SARS-CoV-2 from almost two million genome sequences on the GISAID repositor…