Brinkman AM*, Klaren WD*, Feifarek DJ, Hillwalker W, Jones F, Zorn KM, Ekins S. Use of a weighted scheme for the interpretation and contextualization of in vitro and in silico-derived estrogenic endpoints. Society of Toxicology Annual Meeting, virtual (*equal contributors), 2020.

View Abstract

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.

View Abstract

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 436:152427, doi: 10.1016/j.tox.2020.152427. PMID: 32145346.

View Abstract

Keele GR, Quach BC, Israel JW, Chappell GA, Lewis L, Safi A, et al. 2020. Integrative QTL analysis of gene expression and chromatin accessibility identifies multi-tissue patterns of genetic regulation. PLoS Genet 16(1):e1008537, doi: 10.1371/journal.pgen.1008537.

View Abstract

Mavunda K, Jiang X, Ambrose CS. 2020. Prevalence and clinical characteristics of perinatal chronic lung disease by infant gestational age. J Neonatal-Perinatal Med, DOI: 10.3233/NPM-200412.

View Abstract

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, PMID: 32701041.

View Abstract

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, PMID: 32857505.

View Abstract

House JS, Grimm FA, Klaren WD, Dalzell A, Kuchi S, Zhang S, Lenz K, Boogaard PJ, Ketelsegers HB, Gant TW, Wright FA, Rusyn I. 2020. Grouping of UVCB substances with new approach methodologies (NAMs) data. ALTEX 38(1):123–137, PMID: 33086383 [preprint].

View Abstract

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, PMID: 33207874.

View Abstract

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, PMID: 33085465.

View Abstract