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Metabonomic, transcriptomic, and genomic variation of a population cohort, , , , , , , , , и 8 other автор(ы). Molecular Systems Biology, (21.12.2010)Multiple Output Regression with Latent Noise., , , , , , , , , и . J. Mach. Learn. Res., (2016)Efficient Estimation and Applications of Cross-Validated Genetic Predictions to Polygenic Risk Scores and Linear Mixed Models., , , , , , , , , и . J. Comput. Biol., 27 (4): 599-612 (2020)Application of Quantitative Artificial Neural Network Analysis to 2D NMR Spectra of Hydrocarbon Mixtures., , , и . J. Chem. Inf. Comput. Sci., 42 (6): 1343-1346 (2002)A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic data., , , , , , , , и . BMC Bioinform., (2007)Bayesian Information Sharing Between Noise And Regression Models Improves Prediction of Weak Effects., , , , , , , и . CoRR, (2013)Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression., , , , , , , , , и 8 other автор(ы). Bioinform., 30 (14): 2026-2034 (2014)Genetic and environmental perturbations lead to regulatory decoherence, , , , , , , , , и 1 other автор(ы). Elife, (2019)Efficient Estimation and Applications of Cross-Validated Genetic Predictions., , , , , , , , , и . RECOMB, том 11467 из Lecture Notes in Computer Science, стр. 308-310. Springer, (2019)