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41.
Quell, J. et al.: Automated pathway and reaction prediction facilitates in silico identification of unknown metabolites in human cohort studies. J. Chromatogr. B 1071, 58-67 (2017)
42.
Rueedi, R.* et al.: Metabomatching: Using genetic association to identify metabolites in proton NMR spectroscopy. PLoS Comput. Biol. 13, e1005839:e1005839 (2017)
43.
Sekula, P.* et al.: From discovery to translation: Characterization of c-mannosyltryptophan and pseudouridine as markers of kidney function. Sci. Rep. 7:17400 (2017)
44.
St John-Williams, L.* et al.: Targeted metabolomics and medication classification data from participants in the ADNI1 cohort. Sci. Data 4:170140 (2017)
45.
Suhre, K.* et al.: Connecting genetic risk to disease end points through the human blood plasma proteome. Nat. Commun. 8:14357 (2017)
46.
Toledo, J.B.* et al.: Metabolic network failures in Alzheimer's disease-A biochemical road map. Alzheimers Dement. 13, 965-984 (2017)
47.
Adam, J. et al.: Metformin effect on non-targeted metabolite profiles in patients with type 2 diabetes and multiple murine tissues. Diabetes 65, 3776-3785 (2016)
48.
Altmaier, E. et al.: The pharmacogenetic footprint of ACE inhibition: A population-based metabolomics study. PLoS ONE 11:e0153163 (2016)
49.
Beger, R.D.* et al.: Metabolomics enables precision medicine: “A White Paper, Community Perspective”. Metabolomics 12, 149 (2016)
50.
Fall, T.* et al.: Non-targeted metabolomics combined with genetic analyses identifies bile acid synthesis and phospholipid metabolism as being associated with incident type 2 diabetes. Diabetologia 59, 2114-2124 (2016)
51.
Knacke, H.* et al.: Metabolic fingerprints of circulating IGF-I and the IGF-I/IGFBP-3 ration: A multi-fluid metabolomics study. J. Clin. Endocrinol. Metab. 101, 4730-4742:jc20162588 (2016)
52.
Lacruz, M.E.* et al.: Cardiovascular risk factors associated with blood metabolite concentrations and their alterations over a 4-year period in a population-based cohort. Circ. Cardiovasc. Genet. 9, 487-494 (2016)
53.
Much, D. et al.: Lactation is associated with altered metabolomic signatures in women with gestational diabetes. Diabetologia 59, 2193-2202 (2016)
54.
Much, D. et al.: Lactation is associated with altered metabolomic signatures in women with gestational diabetes. Diabetologia 59, S187-S187 (2016)
55.
Muschaweckh, A. et al.: Antigen-dependent competition shapes the local repertoire of tissue-resident memory CD8+ T cells. J. Exp. Med. 213, 3075-3086 (2016)
56.
Pallister, T.* et al.: Metabolites of milk intake: A metabolomic approach in UK twins with findings replicated in two European cohorts. Eur. J. Nutr. 56, 2379-2391 (2016)
57.
Schulte, E.C. et al.: Alterations in lipid and inositol metabolisms in two dopaminergic disorders. PLoS ONE 11:e0147129 (2016)
58.
Sekula, P.* et al.: A metabolome-wide association study of kidney function and disease in the general population. J. Am. Soc. Nephrol. 27, 1175-1188 (2016)
59.
Suhre, K. ; Raffler, J. & Kastenmüller, G.: Biochemical insights from population studies with genetics and metabolomics. Arch. Biochem. Biophys. 589, 168-176 (2016)
60.
Vehmas, A.P.* et al.: Liver lipid metabolism is altered by increased circulating estrogen to androgen ratio in male mouse. J. Proteomics 133, 66-75 (2016)