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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.

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Title: 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.
Authors: Howey, Richard1,2 (AUTHOR), Adam, Jonathan3 (AUTHOR), Adamski, Jerzy4,5,6 (AUTHOR), Atabaki, Natalie N.7,8,9 (AUTHOR), Brunak, Søren10,11 (AUTHOR), Chmura, Piotr Jaroslaw10 (AUTHOR), De Masi, Federico12 (AUTHOR), Dermitzakis, Emmanouil T.13 (AUTHOR), Fernandez-Tajes, Juan J.14 (AUTHOR), Forgie, Ian M.15 (AUTHOR), Franks, Paul W.9,16 (AUTHOR), Giordano, Giuseppe N.9 (AUTHOR), Haid, Mark17 (AUTHOR), Hansen, Torben7 (AUTHOR), Hansen, Tue H.18,19 (AUTHOR), Harms, Peter P.20 (AUTHOR), Hattersley, Andrew T.21,22 (AUTHOR), Hong, Mun-gwan23 (AUTHOR), Jacobsen, Ulrik Plesner10 (AUTHOR), Jones, Angus G.21,22 (AUTHOR)
Source: PLoS Genetics. 7/15/2025, Vol. 21 Issue 7, p1-20. 20p.
Database: Academic Search Ultimate
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