Detailed information

Hackl, J., & Huang, X. (2025). Revisiting adaptive introgression at the HLA genes in Lithuanian genomes with machine learning. Infection, Genetics and Evolution, 127, Article 105708. https://doi.org/10.1016/j.meegid.2024.105708

PERE, GELABERT., Bickle, P. F., Hofmann, D., Teschler-Nicola, M. E., Anders, A., Huang, X., Hämmerle, M., Olalde, I., Fournier, R., Ringbauer, H., Akbari, A., Cheronet, O., Lazaridis, I., Broomandkhoshbacht, N., Fernandes, D. M., Buttinger, K., Callan, K., Candilio, F., Morante, G. B., ... Reich, D. (2024). Social and genetic diversity in first farmers of central Europe. Nature Human Behaviour. https://doi.org/10.1038/s41562-024-02034-z

Huang, X., Rymbekova, A., Dolgova, O., Lao, O., & Kuhlwilm, M. (2024). Harnessing deep learning for population genetic inference. Nature Reviews. Genetics, 25(1), 61–78. https://doi.org/10.1038/s41576-023-00636-3

Pawar, H., Rymbekova, A., Cuadros-Espinoza, S., Huang, X., Manuel, M. D., Valk, T. V. D., Lobon, I., Alvarez-Estape, M., Haber, M., Dolgova, O., Han, S., Esteller-Cucala, P., Juan, D., Ayub, Q., Garcia, R. B., Kelley, J., Cornejo, O. E., Lao, O., Andrés, A. M., ... Kuhlwilm, M. (2023). Ghost admixture in eastern gorillas. Nature Ecology & Evolution, 7(9), 1503-1514. https://doi.org/10.1038/s41559-023-02145-2

Lauterbur, M. E., Cavassim, M. I., Gladstein, A., Gower, G., Pope, N., Tsambos, G., Adrion, J., Belsare, S., Biddanda, A., Caudill, V., Cury, J., Echevarria, I., Haller, B., Hasan, A., Huang, X., Iasi, L., Noskova, E., Obsteter, J., Pavinato, V., ... Gronau, I. (2023). Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations. eLife, Article 84874. https://doi.org/10.7554/eLife.84874.3

Huang, X., Kruisz, P., & Kuhlwilm, M. (2022). sstar: A Python package for detecting archaic introgression from population genetic data with S*. Molecular Biology and Evolution, 39(11), Article msac212. https://doi.org/10.1101/2022.03.10.483765, https://doi.org/10.1093/molbev/msac212