데이터셋 상세
미국
Conolly, R.B., Ankley, G.T., Cheng, WY., Mayo, M.L., Miller, D.H., Perkins, E.J., Villeneuve, D.L., and Watanable, K.H. (2017). Quantitative adverse outcome pathways and their application ot predictive toxicology. Environ. Sci. Technol. 51, 4661–4672
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).
데이터 정보
연관 데이터
Conolly, R.B., Ankley, G.T., Cheng, WY., Mayo, M.L., Miller, D.H., Perkins, E.J., Villeneuve, D.L., and Watanable, K.H. (2017). Quantitative adverse outcome pathways and their application ot predictive toxicology. Environ. Sci. Technol. 51, 4661–4672
공공데이터포털
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).
Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods
공공데이터포털
Dataset for "Nicolas Chantel I., Linakis Matthew W., Minto Melyssa S., Mansouri Kamel, Clewell Rebecca A., Yoon Miyoung, Wambaugh John F., Patlewicz Grace, McMullen Patrick D., Andersen Melvin E., Clewell III Harvey J, Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods, Frontiers in Pharmacology, 13, 2022, https://www.frontiersin.org/articles/10.3389/fphar.2022.980747,10.3389/fphar.2022.980747"
Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods
공공데이터포털
Dataset for "Nicolas Chantel I., Linakis Matthew W., Minto Melyssa S., Mansouri Kamel, Clewell Rebecca A., Yoon Miyoung, Wambaugh John F., Patlewicz Grace, McMullen Patrick D., Andersen Melvin E., Clewell III Harvey J, Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods, Frontiers in Pharmacology, 13, 2022, https://www.frontiersin.org/articles/10.3389/fphar.2022.980747,10.3389/fphar.2022.980747"
Uncertainty Estimation Strategies for Quantitative Non-Targeted Analysis
공공데이터포털
N/A. This dataset is associated with the following publication: Groff, L., J. Grossman, A. Kruve, J. Minucci, C. Lowe, J. McCord, D. Kapraun, K. Phillips, S. Purucker, A. Chao, C. Ring, A. Williams, and J. Sobus. Uncertainty estimation strategies for quantitative non-targeted analysis. Analytical and Bioanalytical Chemistry. Springer, New York, NY, USA, 414(17): 4919-4933, (2022).
Uncertainty Estimation Strategies for Quantitative Non-Targeted Analysis
공공데이터포털
N/A. This dataset is associated with the following publication: Groff, L., J. Grossman, A. Kruve, J. Minucci, C. Lowe, J. McCord, D. Kapraun, K. Phillips, S. Purucker, A. Chao, C. Ring, A. Williams, and J. Sobus. Uncertainty estimation strategies for quantitative non-targeted analysis. Analytical and Bioanalytical Chemistry. Springer, New York, NY, USA, 414(17): 4919-4933, (2022).
Analogue search results for p,p'-DDD
공공데이터포털
The dataset contains the outputs for the analogue searches conducted for the chemical of interest, p,p'-DDD. This dataset is associated with the following publication: Lizarraga, L., J. Dean, J. Kaiser, S. Wesselkamper, J. Lambert, and J. Zhao. A Case Study on the Application of An Expert-driven Read-Across Approach in Support of Quantitative Risk Assessment of p,p’-Dichlorodiphenyldichloroethane. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 103: 301-313, (2019).
Toxicity by descent: a comparative approach for chemical hazard assessment
공공데이터포털
Data for "John K. Colbourne, Joseph R. Shaw, Elena Sostare, Claudia Rivetti, Romain Derelle, Rosemary Barnett, Bruno Campos, Carlie LaLone, Mark R. Viant, Geoff Hodges, Toxicity by descent: A comparative approach for chemical hazard assessment, Environmental Advances, Volume 9, 2022, 100287, ISSN 2666-7657, https://doi.org/10.1016/j.envadv.2022.100287". This dataset is associated with the following publication: Colbourne, J., J. Shaw, E. Sostare, C. Rivetti, R. Derelle, R. Barnett, B. Campos, C. Lalone, M. Viant, and G. Hodges. Toxicity by descent: a comparative approach for chemical hazard assessment. Environmental Advances. Elsevier B.V., Amsterdam, NETHERLANDS, 9: 100287, (2022).
Toxicity by descent: a comparative approach for chemical hazard assessment
공공데이터포털
Data for "John K. Colbourne, Joseph R. Shaw, Elena Sostare, Claudia Rivetti, Romain Derelle, Rosemary Barnett, Bruno Campos, Carlie LaLone, Mark R. Viant, Geoff Hodges, Toxicity by descent: A comparative approach for chemical hazard assessment, Environmental Advances, Volume 9, 2022, 100287, ISSN 2666-7657, https://doi.org/10.1016/j.envadv.2022.100287". This dataset is associated with the following publication: Colbourne, J., J. Shaw, E. Sostare, C. Rivetti, R. Derelle, R. Barnett, B. Campos, C. Lalone, M. Viant, and G. Hodges. Toxicity by descent: a comparative approach for chemical hazard assessment. Environmental Advances. Elsevier B.V., Amsterdam, NETHERLANDS, 9: 100287, (2022).
Demonstrating the Use of Non-targeted Analysis for Identification of Unknown Chemicals in Rapid Response Scenarios
공공데이터포털
John T. Sloop, Alex Chao, Jennifer Gundersen, Allison L. Phillips, Jon R. Sobus, Elin M. Ulrich, Antony J. Williams, and Seth R. Newton, Environmental Science & Technology 2023 57 (8), 3075-3084, DOI: 10.1021/acs.est.2c06804. This dataset is associated with the following publication: Sloop, J., A. Chao, J. Gundersen, A. Flynn, J. Sobus, E. Ulrich, A. Williams, and S. Newton. Demonstrating the Use of Non-targeted Analysis for Identification of Unknown Chemicals in Rapid Response Scenarios. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 57(8): 3075-3084, (2023).
Demonstrating the Use of Non-targeted Analysis for Identification of Unknown Chemicals in Rapid Response Scenarios
공공데이터포털
John T. Sloop, Alex Chao, Jennifer Gundersen, Allison L. Phillips, Jon R. Sobus, Elin M. Ulrich, Antony J. Williams, and Seth R. Newton, Environmental Science & Technology 2023 57 (8), 3075-3084, DOI: 10.1021/acs.est.2c06804. This dataset is associated with the following publication: Sloop, J., A. Chao, J. Gundersen, A. Flynn, J. Sobus, E. Ulrich, A. Williams, and S. Newton. Demonstrating the Use of Non-targeted Analysis for Identification of Unknown Chemicals in Rapid Response Scenarios. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 57(8): 3075-3084, (2023).
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