Maria De Iorio
Maria De Iorio
Professor of Biostatistics, National University of Singapore
Overená e-mailová adresa na:
Citované v
Citované v
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
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
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
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
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
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
Bayesian nonparametric nonproportional hazards survival modeling
M De Iorio, WO Johnson, P Müller, GL Rosner
Biometrics 65 (3), 762-771, 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
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
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
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
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
Significance testing in ridge regression for genetic data
E Cule, P Vineis, M De Iorio
BMC bioinformatics 12, 1-15, 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
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
Ridge regression in prediction problems: automatic choice of the ridge parameter
E Cule, M De Iorio
Genetic epidemiology 37 (7), 704-714, 2013
Importance sampling on coalescent histories. I
M De Iorio, RC Griffiths
Advances in Applied Probability 36 (2), 417-433, 2004
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
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
Importance sampling on coalescent histories. II: Subdivided population models
M De Iorio, RC Griffiths
Advances in Applied Probability 36 (2), 434-454, 2004
Systém momentálne nemôže vykonať operáciu. Skúste to neskôr.
Články 1–20