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1.
Spracklen, C.N.* et al.: Exome-Derived Adiponectin-Associated Variants Implicate Obesity and Lipid Biology. Am. J. Hum. Genet. 105, 15-28 (2019)
2.
Do, K.T. et al.: Characterization of missing values in untargeted MS-based metabolomics data and evaluation of missing data handling strategies. Metabolomics 14:128 (2018)
3.
Lee, H.K. et al.: Allele-specific quantitative proteomics unravels molecular mechanisms modulated by cis-regulatory PPARG locus variation. Nucleic Acids Res. 45, 3266-3279 (2017)
4.
Molnos, S. et al.: Metabolite ratios as potential biomarkers for type 2 diabetes: A DIRECT study. Diabetologia 61, 117-129 (2017)
5.
Molnos, S. et al.: pulver: An R package for parallel ultra-rapid p-value computation for linear regression interaction terms. BMC Bioinformatics 18:429 (2017)
6.
Reitmeir, P. et al.: Common eye diseases in older adults of Southern Germany: Results from the KORA-Age Study. Age Ageing 46, 481-486 (2017)
7.
't Hart, L.M.* et al.: A metabolite ratio associates with measures of insulin secretion and altered risk of type 2 diabetes; a DIRECT study. Diabetologia 59, S142-S143 (2016)
8.
Kriebel, J. et al.: Association between DNA methylation in whole blood and measures of glucose metabolism: Kora F4 study. PLoS ONE 11:e0152314 (2016)