Human metabolic phenotype diversity and its association with diet and blood pressure E Holmes, RL Loo, J Stamler, M Bictash, IKS Yap, Q Chan, T Ebbels, ... Nature 453 (7193), 396-400, 2008 | 1217 | 2008 |
An ANOVA model for dependent random measures M De Iorio, P Müller, GL Rosner, SN MacEachern Journal of the American Statistical Association 99 (465), 205-215, 2004 | 453 | 2004 |
Simultaneous analysis of all SNPs in genome-wide and re-sequencing association studies CJ Hoggart, JC Whittaker, M De Iorio, DJ Balding PLoS genetics 4 (7), e1000130, 2008 | 411 | 2008 |
Review and evaluation of penalised regression methods for risk prediction in low‐dimensional data with few events M Pavlou, G Ambler, S Seaman, M De Iorio, RZ Omar Statistics in medicine 35 (7), 1159-1177, 2016 | 302 | 2016 |
Genome‐wide significance for dense SNP and resequencing data CJ Hoggart, TG Clark, M De Iorio, JC Whittaker, DJ Balding Genetic Epidemiology: The Official Publication of the International Genetic …, 2008 | 268 | 2008 |
Optimal Bayesian design by inhomogeneous Markov chain simulation P Müller, B Sansó, M De Iorio Journal of the American Statistical Association 99 (467), 788-798, 2004 | 213 | 2004 |
Bayesian nonparametric nonproportional hazards survival modeling M De Iorio, WO Johnson, P Müller, GL Rosner Biometrics 65 (3), 762-771, 2009 | 212 | 2009 |
Bayesian deconvolution and quantification of metabolites in complex 1D NMR spectra using BATMAN J Hao, M Liebeke, W Astle, M De Iorio, JG Bundy, TMD Ebbels Nature protocols 9 (6), 1416-1427, 2014 | 210 | 2014 |
BATMAN—an R package for the automated quantification of metabolites from nuclear magnetic resonance spectra using a Bayesian model J Hao, W Astle, M De Iorio, TMD Ebbels Bioinformatics 28 (15), 2088-2090, 2012 | 192 | 2012 |
Opening up the" Black Box": Metabolic phenotyping and metabolome-wide association studies in epidemiology M Bictash, TM Ebbels, Q Chan, RL Loo, IKS Yap, IJ Brown, M De Iorio, ... Journal of clinical epidemiology 63 (9), 970-979, 2010 | 176 | 2010 |
Meeting-in-the-middle using metabolic profiling–a strategy for the identification of intermediate biomarkers in cohort studies M Chadeau-Hyam, TJ Athersuch, HC Keun, M De Iorio, TMD Ebbels, ... Biomarkers 16 (1), 83-88, 2011 | 147 | 2011 |
Metabolic profiling and the metabolome-wide association study: significance level for biomarker identification M Chadeau-Hyam, TMD Ebbels, IJ Brown, Q Chan, J Stamler, CC Huang, ... Journal of proteome research 9 (9), 4620-4627, 2010 | 142 | 2010 |
Ridge regression in prediction problems: automatic choice of the ridge parameter E Cule, M De Iorio Genetic epidemiology 37 (7), 704-714, 2013 | 141 | 2013 |
Significance testing in ridge regression for genetic data E Cule, P Vineis, M De Iorio BMC bioinformatics 12, 1-15, 2011 | 138 | 2011 |
Sequence-level population simulations over large genomic regions CJ Hoggart, M Chadeau-Hyam, TG Clark, R Lampariello, JC Whittaker, ... Genetics 177 (3), 1725-1731, 2007 | 134 | 2007 |
Metabolome-wide association study identifies multiple biomarkers that discriminate north and south Chinese populations at differing risks of cardiovascular disease: INTERMAP study IKS Yap, IJ Brown, Q Chan, A Wijeyesekera, I Garcia-Perez, M Bictash, ... Journal of proteome research 9 (12), 6647-6654, 2010 | 133 | 2010 |
Conserved Mosquito/Parasite Interactions Affect Development of Plasmodium falciparum in Africa AM Mendes, T Schlegelmilch, A Cohuet, P Awono-Ambene, M De Iorio, ... PLoS pathogens 4 (5), e1000069, 2008 | 124 | 2008 |
Importance sampling on coalescent histories. I M De Iorio, RC Griffiths Advances in Applied Probability 36 (2), 417-433, 2004 | 124 | 2004 |
Metabolic profiling of polycystic ovary syndrome reveals interactions with abdominal obesity A Couto Alves, B Valcarcel, VP Mäkinen, L Morin-Papunen, S Sebert, ... International Journal of Obesity 41 (9), 1331-1340, 2017 | 108 | 2017 |
Importance sampling on coalescent histories. II: Subdivided population models M De Iorio, RC Griffiths Advances in Applied Probability 36 (2), 434-454, 2004 | 88 | 2004 |