Aoxing Liu

Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker

Vabalas, A., Hartonen, T., Vartiainen, P., Jukarainen, S., Viippola, E., Rodosthenous, R. S., Liu, A., Hägg, S., Perola, M. & Ganna, A., 2024, I: Nature Aging. 4, s. 1014–1027 22 s.

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Genetic drivers and cellular selection of female mosaic X chromosome loss

FinnGen, Estonian Biobank Research Team, Breast Cancer Association Consortium, Million Veteran Program, Liu, A., Genovese, G., Zhao, Y., Pirinen, M., Zekavat, S. M., Kentistou, K. A., Yang, Z., Yu, K., Vlasschaert, C., Liu, X., Brown, D. W., Hudjashov, G., Gorman, B. R., Dennis, J., Zhou, W. & Momozawa, Y. & 25 andra, Pyarajan, S., Tuzov, V., Pajuste, F. D., Aavikko, M., Sipilä, T. P., Ghazal, A., Huang, W. Y., Freedman, N. D., Song, L., Gardner, E. J., Sankaran, V. G., Palotie, A., Ollila, H. M., Tukiainen, T., Chanock, S. J., Mägi, R., Natarajan, P., Daly, M. J., Bick, A., McCarroll, S. A., Terao, C., Loh, P. R., Ganna, A., Perry, J. R. B. & Machiela, M. J., 1 juli 2024, I: Nature. 631, 8019, s. 134-141 8 s.

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Multi-ancestry genome-wide association study of kidney cancer identifies 63 susceptibility regions

Purdue, M. P., Dutta, D., Machiela, M. J., Gorman, B. R., Winter, T., Okuhara, D., Cleland, S., Ferreiro-Iglesias, A., Scheet, P., Liu, A., Wu, C., Antwi, S. O., Larkin, J., Zequi, S. C., Sun, M., Hikino, K., Hajiran, A., Lawson, K. A., Cárcano, F. & Blanchet, O. & 112 andra, Shuch, B., Nepple, K. G., Margue, G., Sundi, D., Diver, W. R., Folgueira, M. A. A. K., van Bokhoven, A., Neffa, F., Brown, K. M., Hofmann, J. N., Rhee, J., Yeager, M., Cole, N. R., Hicks, B. D., Manning, M. R., Hutchinson, A. A., Rothman, N., Huang, W. Y., Linehan, W. M., Lori, A., Ferragu, M., Zidane-Marinnes, M., Serrano, S. V., Magnabosco, W. J., Vilas, A., Decia, R., Carusso, F., Graham, L. S., Anderson, K., Bilen, M. A., Arciero, C., Pellegrin, I., Ricard, S., Scelo, G., Banks, R. E., Vasudev, N. S., Soomro, N., Stewart, G. D., Adeyoju, A., Bromage, S., Hrouda, D., Gibbons, N., Patel, P., Sullivan, M., Protheroe, A., Nugent, F. I., Fournier, M. J., Zhang, X., Martin, L. J., Komisarenko, M., Eisen, T., Cunningham, S. A., Connolly, D. C., Uzzo, R. G., Zaridze, D., Mukeria, A., Holcatova, I., Hornakova, A., Foretova, L., Janout, V., Mates, D., Jinga, V., Rascu, S., Mijuskovic, M., Savic, S., Milosavljevic, S., Gaborieau, V., Abedi-Ardekani, B., McKay, J., Johansson, M., Phouthavongsy, L., Hayman, L., Li, J., Lungu, I., Bezerra, S. M., Souza, A. G., Sares, C. T. G., Reis, R. B., Gallucci, F. P., Cordeiro, M. D., Pomerantz, M., Lee, G. S. M., Freedman, M. L., Jeong, A., Greenberg, S. E., Sanchez, A., Thompson, R. H., Sharma, V., Thiel, D. D., Ball, C. T., Abreu, D., Lam, E. T., Nahas, W. C., Master, V. A., Patel, A. V., Bernhard, J. C., Freedman, N. D., Bigot, P., Reis, R. M., Colli, L. M., Finelli, A., Manley, B. J., Terao, C., Choueiri, T. K., Carraro, D. M., Houlston, R., Eckel-Passow, J. E., Abbosh, P. H., Ganna, A., Brennan, P., Gu, J. & Chanock, S. J., maj 2024, I: Nature Genetics. 56, 5, s. 809-818 10 s.

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Prevalence, Morbidity, and Mortality of Men with Sex Chromosome Aneuploidy in the Million Veteran Program Cohort

Davis, S. M., Teerlink, C., Lynch, J. A., Gorman, B. R., Pagadala, M., Liu, A., Panizzon, M. S., Merritt, V. C., Genovese, G., Ross, J. L. & Hauger, R. L., 29 mars 2024, I: JAMA Network Open. 7, 3, 14 s., E244113.

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Data Resource Profile: Nationwide registry data for high-throughput epidemiology and machine learning (FinRegistry)

Finn Gen, Viippola, E., Kuitunen, S., Rodosthenous, R. S., Vabalas, A., Hartonen, T., Vartiainen, P., Demmler, J., Vuorinen, A.-L., Liu, A., Havulinna, A. S., Llorens, V., Detrois, K. E., Wang, F., Ferro, M., Karvanen, A., German, J., Jukarainen, S., Gracia-Tabuenca, J. & Hiekkalinna, T. & 15 andra, Koskelainen, S., Kiiskinen, T., Lahtela, E., Lemmelä, S., Paajanen, T., Siirtola, H., Reeve, M. P., Kristiansson, K., Brunfeldt, M., Aavikko, M., Perola, M., Ganna, A., Kaprio, J., Mäkitie, A. & Tienari, P., 2 aug. 2023, I: International Journal of Epidemiology. 52, 4, s. e195–e200 6 s.

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Aoxing Liu

Personlig profil

Vetenskapsgrenar

Internationellt och inhemskt samarbete

Fördjupning

Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker

Genetic drivers and cellular selection of female mosaic X chromosome loss

Multi-ancestry genome-wide association study of kidney cancer identifies 63 susceptibility regions

Prevalence, Morbidity, and Mortality of Men with Sex Chromosome Aneuploidy in the Million Veteran Program Cohort

Data Resource Profile: Nationwide registry data for high-throughput epidemiology and machine learning (FinRegistry)

Aoxing Liu

Personlig profil

Vetenskapsgrenar

Internationellt och inhemskt samarbete

Publikationer

Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker

Genetic drivers and cellular selection of female mosaic X chromosome loss

Multi-ancestry genome-wide association study of kidney cancer identifies 63 susceptibility regions

Prevalence, Morbidity, and Mortality of Men with Sex Chromosome Aneuploidy in the Million Veteran Program Cohort

Data Resource Profile: Nationwide registry data for high-throughput epidemiology and machine learning (FinRegistry)