Selected Publications

* Corresponding author

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Preprints

2026

Koça A, Stöckl A, Chen S, Kuhlwilm M*, Huang X*. sstar2: A Python package for S*-based archaic introgression detection with machine learning. bioRxiv: 2026.05.31.729079.

2026

Chen S, Huang X*. selscape: A Snakemake workflow for investigating genomic landscapes of natural selection. bioRxiv: 2026.02.28.708717.

2026

Huang X*, Hackl J, Pawar H, Kuhlwilm M*. GAISHI: A Python package for detecting ghost introgression with machine learning. bioRxiv: 2026.01.31.703038.

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Research

2026

Huang X*, Chen S, Han S, Kuhlwilm M*. Genomic landscapes of natural selection in great apes. Genome Biology.

2025

Huang X*, Chen S, Hackl J, Kuhlwilm M*. SAI: A Python package for statistics for adaptive introgression. Molecular Biology and Evolution 42: msaf295.

2022

Huang X*, Kruisz P, Kuhlwilm M*. sstar: A Python package for detecting archaic introgression from population genetic data with S*. Molecular Biology and Evolution 39: msac212.

2021

Huang X, Fortier AL, Coffman AJ, Struck TJ, Irby MN, James JE, León-Burguete JE, Ragsdale AR, Gutenkunst RN*. Inferring genome-wide correlations of mutation fitness effects between populations. Molecular Biology and Evolution 38: 4588–4602.

2021

Huang X*, Wang S, Jin L*, He Y*. Dissecting dynamics and differences of selective pressures in the evolution of human pigmentation. Biology Open 10: bio056523.

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Reviews

2025

Huang X*, Hackl J, Kuhlwilm M*. Decoding genomic landscapes of introgression. Trends in Genetics 41: 1096–1108.

2024

Huang X*, Rymbekova A, Dolgova O, Lao O*, Kuhlwilm M*. Harnessing deep learning for population genetic inference. Nature Reviews Genetics 25: 61–78.