M.C. Cornelis

Discipline

Anthropologie biologique (2) Economies et finances (1)

Type de document

Articles (12) Autres (1)

Co-auteur

Date

Source

Mot-clé

association (9) Genes (9) Social groups (9) Meta-analysis (9) Human beings (6) Heredity (6) Genealogy (6) roman (5) Family (4) risque (3) effet (3) maladie (3) âge (3) règlement (3) Development (3) Women (3) Risk (3) Glucose (3) Glomerular filtration rate (3) Blood pressure (3) Age (3) Addition (3) Regulation (3) Women (3) Age (3) Influence (3) Risk factors (3) maladie (3) temps (durée) (2) tabagisme (2)

Documents écrit par M.C. Cornelis (12) | parle de M.C. Cornelis (0)

Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention.
Z. Wang et al.
Corrigendum: 1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function.
M. Gorski et al. (26 mai 2017)
1000 Genomes-based meta-analysis identifies 10 novel loci for kidney function.
M. Gorski et al. (28 avr. 2017)
Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.
C. Pattaro et al. (2016)
Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption
M.C. Cornelis et al.
Directional dominance on stature and cognition in diverse human populations.
P.K. Joshi et al. (2015)
Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders.
M. den Hoed et al. (2013)
A genome-wide association study of early menopause and the combined impact of identified variants.
J.R. Perry et al. (2013)
Genome-wide association and functional follow-up reveals new loci for kidney function.
C. Pattaro et al. (2012)
Meta-analyses identify 13 loci associated with age at menopause and highlight DNA repair and immune pathways.
L. Stolk et al. (2012)
Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk.
G.B. Ehret et al. (2011)
Thirty new loci for age at menarche identified by a meta-analysis of genome-wide association studies.
C.E. Elks et al. (2010)