Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.
Allesøe, Rosa Lundbye, Lundgaard, A., Hernández Medina, R., Aguayo-Orozco, Alejandro, Johansen, J., Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, L., Biel, J., Brasas, Valentas, Webel, Henry, Benros, M., Pedersen, A., Chmura, Piotr Jaroslaw, Jacobsen, U., Mari, Andrea, Koivula, R., Mahajan, Anubha, Vinuela, A., Tajes, Juan Fernandez, Sharma, Sapna, Haid, M., Hong, M., Musholt, Petra B, De Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, G., Bell, Jimmy, Thomas, E.L., Frost, G., Thomsen, Henrik, Hansen, Elizaveta, Hansen, T., Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T, 't Hart, Leen M, Pattou, Francois, Raverdy, Violeta, Brage, Soren, Kokkola, Tarja, Heggie, Alison, McEvoy, Donna, Mourby, Miranda, Kaye, J., Hattersley, A., McDonald, Timothy, Ridderstråle, M., Walker, Mark, Forgie, Ian, Giordano, Giuseppe N, Pavo, Imre, Ruetten, Hartmut, Pedersen, O., Hansen, T., Dermitzakis, Emmanouil, Franks, Paul W, Schwenk, J., Adamski, Jerzy, McCarthy, Mark I, Pearson, Ewan, Banasik, Karina, Rasmussen, S., Brunak, S. and IMI DIRECT Consortium 2023. Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models. Nature Biotechnology. 41, pp. 399-408. https://doi.org/10.1038/s41587-022-01520-x