Bayesian network imputation methods applied to multi-omics data identify putative causal relationships in a type 2 diabetes dataset containing incomplete data: An IMI DIRECT Study
Howey, R., Adam, J., Adamski, J., Atabaki, N. N., Brunak, S. R., Chmura, P. J., de Masi, F., Dermitzakis, E. T., Fernandez-Tajes, J. J., Forgie, I. M., Franks, P. W., Giordano, G. N., Haid, M., Hansen, T., Hansen, T. H.,
Harms, P. P., Hattersley, A. T., Hong, M.-G., Jacobsen, U. P. & Jones, A. G.
& 18 others,
Koivula, R. W., Kokkola, T., Mahajan, A., Mari, A., McCarthy, M. I., McDonald, T. J., Musholt, P. B., Pavo, I., Pearson, E. R., Pedersen, O., Ruetten, H., Rutters, F., Schwenk, J. M., Sharma, S., t Hart, L. M., Vestergaard, H., Walker, M. & The IMI DIRECT consortium,
1 Jul 2025,
In: PLoS genetics. 21,
7, e1011776.
Research output: Contribution to journal › Article* › Academic › peer-review