Publications
Matthew Wheeler (43 POSTS)
2025 (2 POSTS)
Artificial intelligence application to critical appraisal of published literature: A case example using the Criteria for Reporting and Evaluating Ecotoxicity Data (CRED) evaluation method
East A, Wheeler M, Kennedy S. Artificial intelligence application to critical appraisal of published literature: A case example using the Criteria for Reporting and Evaluating Ecotoxicity Data (CRED) evaluation method. Poster presentation, Health and Environmental Sciences Institute (HESI) Biannual Meeting, Washington, DC, June 2025.
View AbstractBayesian gene set benchmark dose estimation for “omic” responses
Zilber D, Messier KP, House J, Parham F, Auerbach SS, Wheeler MW. 2025. Bayesian gene set benchmark dose estimation for “omic” responses. Bioinformatics 41(1):btaf008; doi: 10.1093/bioinformatics/btaf008. PMCID: PMC11783320.
View Abstract2024 (4 POSTS)
A hierarchical constrained density regression model for predicting cluster‐level dose‐response
Pennell ML, Wheeler MW, Auerbach SS. 2024. A hierarchical constrained density regression model for predicting cluster‐level dose‐response. Environmetrics 35(7):e2880; doi: 10.1002/env.2880.
View AbstractBioinformatic workflows for deriving transcriptomic points of departure: Current status, data gaps, and research priorities
O’Brien J, Mitchell C, Auerbach S, Doonan L, Ewald J, Everett L, Faranda A, Johnson K, Reardon A, Rooney J., Wheeler MW, et al. 2024. Bioinformatic workflows for deriving transcriptomic points of departure: Current status, data gaps, and research priorities. Toxicol Sci 203(2):147-159; doi: 10.1093/toxsci/kfae145. PMCID: PMC11775421.
View AbstractSystematic update to the mammalian relative potency estimate database and development of best estimate toxic equivalency factors for dioxin-like compounds
Fitch S, Blanchette A, Haws LC, Franke K, Ring C, DeVito M, Wheeler M,… Wikoff DS. 2024. Systematic update to the mammalian relative potency estimate database and development of best estimate toxic equivalency factors for dioxin-like compounds. Regul Toxicol Pharmacol 147(Feb):105571; doi: 10.1016/j.yrtph.2024.105571. PMID: 38244664.
View AbstractThe 2022 World Health Organization reevaluation of human and mammalian toxic equivalency factors for polychlorinated dioxins, dibenzofurans and biphenyls
DeVito M, Bokkers B, van Duursen MBM, van Ede K, Feeley M, Antunes Fernandes Gaspar E, Haws L,… Wheeler M,… Wikoff D, et al. 2024. The 2022 World Health Organization reevaluation of human and mammalian toxic equivalency factors for polychlorinated dioxins, dibenzofurans and biphenyls. Regul Toxicol Pharmacol 146(Jan):105525; doi: 10.1016/j.yrtph.2023.105525. PMID: 37972849.
View Abstract2023 (3 POSTS)
A multi-tiered hierarchical Bayesian approach to derive toxic equivalency factors for dioxin-like compounds
Ring C, Blanchette A, Klaren WD, Fitch S, Haws L, Wheeler MW, DeVito MJ, Walker N, Wikoff D. 2023. A multi-tiered hierarchical Bayesian approach to derive toxic equivalency factors for dioxin-like compounds. Regul Toxicol Pharmacol 143(11):105464; doi: 10.1016/j.yrtph.2023.105464. PMID: 37516304.
View AbstractAn investigation of non-informative priors for Bayesian dose-response modeling
Wheeler MW. 2023. An investigation of non-informative priors for Bayesian dose-response modeling. Regul Toxicol Pharmacol 141(June):105389; doi: 10.1016/j.yrtph.2023.105389. PMCID: PMC10436774.
View AbstractToxicR: A computational platform in R for computational toxicology and dose–response analyse
Wheeler MW, Lim S, House JS, Shockley KR, Bailer AJ, Fostel J, Yang L, Talley D, Raghuraman A, Gift JS. 2023. ToxicR: A computational platform in R for computational toxicology and dose–response analyses. Comp Toxicol 25(Feb):100259; doi: 10.1016/j.comtox.2022.100259. PMCID: PMC9997717.
View Abstract2022 (3 POSTS)
Fast increased fidelity samplers for approximate Bayesian Gaussian process regression
Moran KR, Wheeler MW. 2022. Fast increased fidelity samplers for approximate Bayesian Gaussian process regression. J Roy Stat Soc B 84(4):1198-228; doi: 10.1111/rssb.12494. PMCID: 36570797.
View AbstractContinuous model averaging for benchmark dose analysis: Averaging over distributional forms
Wheeler MW, Cortiñas Abrahantes J, Aerts M, Gift JS, Allen Davis J. 2022. Continuous model averaging for benchmark dose analysis: Averaging over distributional forms. Environmetrics 33(5):e2728; doi: 10.1002/env.2728. PMCID: PMC9799099.
View AbstractALOHA: Aggregated local extrema splines for high-throughput dose–response analysis
Davidson SE, Wheeler MW, Auerbach SS, Sivaganesan S, Medvedovic M. 2022. ALOHA: Aggregated local extrema splines for high-throughput dose–response analysis. Comp Toxicol. 21(Feb):100196; doi: 10.1016/j.comtox.2021.100196. PMCID: PMC8785973.
View Abstract2021 (3 POSTS)
Bayesian joint modeling of chemical structure and dose response curves
Moran KR, Dunson D, Wheeler MW, Herring AH. 2021. Bayesian joint modeling of chemical structure and dose response curves. Ann Appl Stat 15(3):1405; doi: 10.214/21-aoas1461. PMCID: PMC9236276.
View AbstractBayesian stacked parametric survival with frailty components and interval‐censored failure times: An application to food allergy risk
Wheeler MW, Westerhout J, Baumert JL, Remington BC. 2021. Bayesian stacked parametric survival with frailty components and interval‐censored failure times: An application to food allergy risk. Risk Anal 41(1):56-66; doi: 10.1111/risa.13585. PMCID: PMC7894991.
View AbstractThe COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring county-level vulnerability using visualization, statistical modeling, and machine learning
Marvel SW, House JS, Wheeler MW, Song K, Zhou Y-H, Wright FA, Chiu WA, Rusyn I, Motsinger-Reif A, Reif DM. 2021. The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: Monitoring county-level vulnerability using visualization, statistical modeling, and machine learning. Environ Health Perspect 129(1):017701; doi: 10.1289/EHP8690. PMCID: PMC7430608
View Abstract2020 (4 POSTS)
Full range of population eliciting dose values for 14 priority allergenic foods and recommendations for use in risk characterization
Houben GF, Baumert JL, Blom WM, Kruizinga AG, Meima MY, Remington BC, Wheeler MW, Westerhout J, Taylor SL. 2020. Full range of population eliciting dose values for 14 priority allergenic foods and recommendations for use in risk characterization. Food Chem Toxicol 146(Dec)111831; doi: 10.1016/j.fct.2020.111831. PMCID: PMC7864389.
View AbstractAn extended and unified modeling framework for benchmark dose estimation for both continuous and binary data
Aerts M, Wheeler MW, Abrahantes JC. 2020. An extended and unified modeling framework for benchmark dose estimation for both continuous and binary data. Environmetrics 31(7):e2630; doi: 10.1002/env.2630. PMCID: PMC9432821.
View AbstractQuantitative risk assessment: Developing a Bayesian approach to dichotomous dose–response uncertainty
Wheeler MW, Blessinger T, Shao K, Allen BC, Olszyk L, Davis JA, Gift JS. 2020. Quantitative risk assessment: Developing a Bayesian approach to dichotomous dose–response uncertainty. Risk Anal 40(9):1706-22; doi: 10.1111/risa.13537. PMCID: PMC7722241.
View AbstractUpdated population minimal eliciting dose distributions for use in risk assessment of 14 priority food allergens
Remington BC, Westerhout J, Meima MY, Blom WM, Kruizinga AG, Wheeler MW, Taylor SL, Houben GF, Baumert JL. 2020. Updated population minimal eliciting dose distributions for use in risk assessment of 14 priority food allergens. Food Chem Toxicol 139(May):111259; doi: 10.1016/j.fct.2020.111259. PMCID: PMC7748293.
View Abstract2019 (2 POSTS)
Quantal risk assessment database: A database for exploring patterns in quantal dose‐response data in risk assessment and its application to develop priors for Bayesian dose‐response analysi
Wheeler MW, Piegorsch WW, Bailer AJ. 2019. Quantal risk assessment database: A database for exploring patterns in quantal dose‐response data in risk assessment and its application to develop priors for Bayesian dose‐response analysis. Risk Anal 39(3):616-29; doi: 10.1111/risa.13218. PMCID: PMC6408269
View Abstract