Publication Topic

Roell K, Koval LE, Boyles R, Patlewicz G, Ring C, Rider CV, Ward-Caviness C, Reif D, et al. 2022. Development of the intelligence and machine learning toolkit (TAME) for introductory data science, chemical-biological analyses, predictive modelling, and database mining for environmental health research. Front Toxicol 4(Jun 22):893924; doi: 10.3389/ftox.2022.893924. PMID: 35812168.

Patlewicz G. 2022. Editorial: Reflections of the QSAR2021 meeting. Comput Toxicol 22(May):100221; doi: 10.1016/j.comtox.2022.100221. PMID: 35252631.

Patlewicz G, Worth AP, Yang C, Zhu T. 2022. Editorial: Advances and refinements in the development and application of threshold of toxicological concern. Front Toxicol 4(Apr 28):882321; doi: 10.3389/ftox.2022.882321. PMID: 35573274.

Williams AJ, Gaines LG, Grulke CM, Lowe CN, Sinclair G, Samano V, Thillainadarajah I, Meyer B, Patlewicz G, Richard AM. 2022. Assembly and curation of list of per- and polyfluoroalkyl substances (PFAS) to support environmental science research. Front Environ Sci 10(Apr 5):1-13; doi: 10.3389/fenvs.2022.850019. PMID: 35936994.

Mansouri K, Karmaus A, Fitzpatrick J, Patlewicz G, Pradeep P, Alberga D et al. 2021. CATMoS: Collaborative acute toxicity modeling suite. Environ Health Perspect 129(4):47013; doi: 10.1289/EHP8495. PMID: 33929906.

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.

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.

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.

Zorn KM, Foil DH, Russo DP, Clark AM, Hillwalker W, Feifarek D, Jones F, Klaren W, Brinkman A, Ekins S. Generation of machine-learning models to anticipate endocrine disruption. Society of Toxicology 59th Annual Meeting, Virtual, 2020.

Bell S, Mansouri K, Phillips J, Chang X, Abedini J, Karmaus AL, Lea I, Rai R, Allen DG, Casey W, Kleinstreuer NC. NCEATM computational tools and resources supporting alternative test method development and evaluation. Abstract #2976-P607, Society of Toxicology 59th Annual Meeting, Anaheim CA, March 2020.