Morris A. Aguilar, John McGuigan, and Molly A. Hall (2021)
Semi-automated NMR Pipeline for Environmental Exposures: New Insights on the Metabolomics of Smokers versus Non-smokers
Pacific Symposium on Biocomputing: 26, 316-327
Passero K, et al (2021)
What about the environment? Leveraging multi-omic datasets to characterize the environment’s role in human health
Pacific Symposium on Biocomputing: 26, 309-315
Zhou J, et al (2020)
Investigation of gene-gene interactions in cardiac traits and serum fatty acid levels in the LURIC Health Study
PloS one: 15(9), e0238304
Passero K, et al (2020)
Phenome-wide association studies on cardiovascular health and fatty acids considering phenotype quality control practices for epidemiological data.
Pacific Symposium on Biocomputing: 25, 659-670
Lucas AM, et al (2019)
CLARITE facilitates the quality control and analysis process for EWAS of metabolic-related traits.
Frontiers in Genetics: 10, 1240
Hall MA, Cole B, Moore JH. (2019)
Gene-Gene Interactions: An Essential Component to Modeling Complexity for Precision Medicine.
Encyclopedia of Bioinformatics and Computational Biology: 2, 171-177
Cole B, Hall MA, Urbanowicz RJ, Gilbert-Diamond D, Moore JH (2018)
Analysis of Gene‐Gene Interactions
Current Protocols in Human Genetics: 95.1, 1-14
Manduchi E, Chesi A, Hall MA, Grant SFA, Moore JH. (2018)
Leveraging putative enhancer-promoter interactions to investigate two-way epistasis in type 2 diabetes GWAS.
Pacific Symposium on Biocomputing: 23, 548-558
Hall MA, et al (2017)
PLATO provides analytic framework for investigating complexity beyond genome-wide association studies
Nature Communications
Hall MA, Moore JH, Ritchie MD (2016)
Embracing complex associations in common traits: Critical considerations for precision medicine
Trends in Genetics: 32, 470-484
Hall MA, Verma SS, Wallace J, Lucas A, et al. (2015)
Biology-driven gene-gene interaction analysis of age-related cataract in the eMERGE Network
Genetic Epidemiology: 39, 376-384
Hall MA, Verma A, Brown-Gentry KD, Goodloe R, et al. (2014)
Detection of pleiotropy through and phenome-wide association study (PheWAS) of epidemiologic data as part of the Environmental Architecture for Genes Linked to Environment (EAGLE) study
PLoS Genetics: 10