A publised mansucript describing a quantitative adverse outcome pathway (qAOP) and its relevance to risk assessment. This dataset is not publicly accessible because: This work describes computational modeling, not acquisition of laboratory data. It can be accessed through the following means: The mansucript is published in Environmental Science and Technology. Format: This ScienceHub entry is associated with the published manuscript:

Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology Rory B. Conolly,*,† Gerald T. Ankley,‡ WanYun Cheng,† Michael L. Mayo,§ David H. Miller,∥ Edward J. Perkins,§ Daniel L. Villeneuve,‡ and Karen H. Watanabe⊥ †U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Integrated Systems Toxicology Division, Research Triangle Park, North Carolina 27709, United States ‡U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, Duluth, Minnesota 55804, United States §Environmental Laboratory, U.S. Army Engineer Research and Development Center, Vicksburg, Mississippi 39180, United States ∥U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, Grosse Isle, Michigan 48138, United States ⊥School of Mathematical and Natural Sciences, Arizona State University, West Campus, Glendale, Arizona 85306, United States

DOI: 10.1021/acs.est.6b06230 Environ. Sci. Technol. 2017, 51, 4661−4672.

This dataset is associated with the following publication: Conolly, R., G. Ankley, W. Cheng, M. Mayo, D. Miller, E. Perkins, D. Villeneuve, and K. Watanabe. Quantitative Adverse Outcome Pathways and Their Application to Predictive Toxicology. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 51(8): 4661-4672, (2017).