2020
Chappell GA, Wikoff DS , Doepker CL, Borghoff SJ . 2020. Lack of potential carcinogenicity for acesulfame potassium — Systematic evaluation and integration of mechanistic data into the totality of the evidence. Food Chem Toxicol 141(July):111375; doi: 10.1016/j.fct.2020.111375 . PMID: 32360221.
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Publication: Manuscripts
/ Topics: carcinogens , Systematic Review
Urban JD , Wikoff DS , Chappell GA, Harris C, Haws LC. 2020. Systematic evaluation of mechanistic data in assessing in utero exposures to trichloroethylene and development of congenital heart defects. Toxicology 436(30 April):152427; doi: 10.1016/j.tox.2020.152427 . PMID: 32145346.
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Publication: Manuscripts
/ Topics: trichloroethylene
Chappell GA, Thompson CM , Wolf JC, Cullen JM, Klaunig JE, Haws LC. 2020. Assessment of the mode of action underlying the effects of GenX in mouse liver and implications for assessing human health risks. Toxicol Pathol 48(3):494–508; doi: 10.1177/0192623320905803 . PMID: 32138627.
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Publication: Manuscripts
/ Topics: mode of action , PFAS , risk assessment
Grimm FA, Klaren WD , Li X, Lehmler HJ, Karmakar M, Robertson LW, Chiu WA. Rusyn I. 2020. Cardiovascular effects of polychlorinated biphenyls and their major metabolites. Environ Health Persp 128(7):77008; doi: 10.1289/EHP7030 . PMID: 32701041.
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Publication: Manuscripts
/ Topics: PCBs
Patlewicz G . 2020. Navigating the minefield of computational toxicology and informatics: Looking back and charting a new horizon. Front Toxicol 2:2; doi: 10.3389/ftox.2020.00002 . PMID: 35296116.
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Publication: Manuscripts
/ Topics: computational toxicology
Zorn KM, Foil DH, Lane TR, Russo DP, Hillwalker W, Feifarek DJ, Jones F, Klaren WD , Brinkman AM, Ekins S. 2020. Machine learning models for estrogen receptor bioactivity and endocrine disruption prediction. Environ Sci Technol 54(19):12202–12213; doi: 10.1021/acs.est.0c03982 . PMID: 32857505.
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Publication: Manuscripts
/ Topics: computational toxicology , modeling
Zorn KM, Foil DH, Lane TR, Hillwalker W, Feifarek DJ, Jones F, Klaren WD , Brinkman AM, Ekins S. 2020. Comparison of machine learning models for the androgen receptor. Environ Sci Technol 54(21):13690–13700; doi: 10.1021/acs.est.0c03984 . PMID: 33085465.
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Publication: Manuscripts
/ Topics: modeling
Zorn KM, Foil DH, Lane TR, Hillwalker W, Feifarek DJ, Jones F, Klaren WD , Brinkman AM, Ekins S. 2020. Comparing machine learning models for aromatase (P450 19A1). Environ Sci Technol 54(23):15546–15555; doi: 10.1021/acs.est.0c05771 . PMID: 33207874.
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