Publication Topic

Leary A, Shah I, Patlewicz G. 2025. An exploration of the use of hybrid fingerprints in Generalized Read-Across and their impact on predictive performance for selected in vivo toxicity outcomes. Comput Toxicol 34(June):100349; doi: 10.1016/j.comtox.2025.100349.

Hagan B, Patlewicz G, Shah I. Metabolic similarity in read-across prediction: A case study using graph convolutional networks to predict genotoxicity outcomes from metabolic networks. Abstract 62, American Society for Cellular and Computation Toxicology 13th Annual Meeting, Research Triangle Park, NC, October 2024.

Leary AJ, Patlewicz G, Shah I. An exploration of the use of hybrid fingerprints in generalized read-across and their impact on predictive performance for selected in vivo toxicity outcomes. Abstract 42, American Society for Cellular and Computation Toxicology 13th Annual Meeting, Research Triangle Park, NC, October 2024.

Patlewicz G. Comparing expert-driven read-across assessments using the generalized read-across framework. Abstract 1110, Society of Toxicology 63^rd Annual Meeting, Salt Lake City, UT, March 2024.

Patlewicz G, Shah I. Towards systematic read-across using Generalised Read-Across (GenRA). American Society for Cellular and Computation Toxicology 11^th Annual Meeting, Chapel Hill, NC, October 2022.

Hagan B, Patlewicz G, Shah I. Metabolic similarity in read-across prediction: A case study in using graph kernels and predicted metabolism information. American Society for Cellular and Computation Toxicology 11^th Annual Meeting, Chapel Hill, NC, October 2022

Bassan A, Alves VM, Amberg A, Anger LT, Auerbach S, Beilke L, Bender A…, Greene N, et al. 2021. In silico approaches in organ toxicity hazard assessment: Current status and future needs in predicting liver toxicity. Computation Toxicol 20(Nov):100187; doi: 10.1016/j.comtox.2021.100187. PMID: 35340402.

Pradeep P, Mansouri K, Patlewicz G, Judson RS. 2017. A systematic evaluation of analogs and automated read-across prediction of estrogenicity: A case study using hindered phenols. Comput Toxicol 4(Nov):22-30; doi: 10.1016/j.comtox.2017.09.001. PMID: 30057968.

Patlewicz G, Helman G, Pradeep P, Shah I. 2017. Navigating through the minefield of read-across tools: A review of in silico tools for grouping. Comput Toxicol 3(Aug):1-18; doi: 10.1016/j.comtox.2017.05.003. PMID: 30221211.

Patlewicz G, Worth AP, Ball N. 2016. Validation of computational methods. Adv Exp Med Biol 856:165-187; doi: 10.1007/978-3-319-33826-2_6. PMID: 27671722.

Shah I, Liu J, Judson RS, Thomas R, Patlewicz G. 2016. Systematically evaluating read-across prediction and performance using a local validity approach characterized by chemical structure and bioactivity information. Reg Toxicol Pharmacol 79(Aug):12-24; doi: 10.1016/j.yrtph.2016.05.008. PMID: 27174420.

Ball N, Cronin MTD, Shen J, Blackburn K, Booth ED, Bouhifd M, Donley E,…, Patlewicz G, et al. 2016. Toward good read-across practice (GRAP) guidance. ALTEX 33(2):149-166; doi: 10.14573/altex.1601251. PMID: 26863606.

Patlewicz G, Ball N, Boogaard P, Becker RA, Hubesch B. 2015. Building scientific confidence in the development and evaluation of read-across. Regul Toxicol Pharmacol 72(1):117-133; doi: 10.1016/j.yrtph.2015.03.015. PMID: 25857293.