A collection of R scripts useful for extracting and analyzing adverse outcome pathway network data from the adverse outcome pathway wiki (aopwiki.org). This dataset is associated with the following publication: Pollesch, N., D. Villeneuve, and J. O'Brien. Extracting and benchmarking emerging adverse outcome pathway knowledge. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 168(2): 349-364, (2019).

The data set provides a set of txt files and cytoscape files that were used to construct the example AOP networks included in the paper. Additionally, a supplementary table file provides all the network statistics discussed in the manuscript (e.g., node degree calculations, betweenness centrality, eccentricity, etc.). This dataset is associated with the following publication: Villeneuve, D., M. Angrish, M. Fortin, I. Katsiadaki, M. Leonard, L. Margiotta-Casaluci, S. Munn, J. O'Brien, N. Pollesch, C. Smith, X. Zhang, and D. Knapen. Adverse outcome pathway networks II: Network analytics. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(6): 1734-1748, (2018).

The data set provides a set of txt files and cytoscape files that were used to construct the example AOP networks included in the paper. Additionally, a supplementary table file provides all the network statistics discussed in the manuscript (e.g., node degree calculations, betweenness centrality, eccentricity, etc.). This dataset is associated with the following publication: Villeneuve, D., M. Angrish, M. Fortin, I. Katsiadaki, M. Leonard, L. Margiotta-Casaluci, S. Munn, J. O'Brien, N. Pollesch, C. Smith, X. Zhang, and D. Knapen. Adverse outcome pathway networks II: Network analytics. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(6): 1734-1748, (2018).

A set of three proposed "hub" key events were used to link together a series of example adverse outcome pathway (AOP) descriptions that were previously not linked in an AOP network. While there are no data associated with this product, the relevant adverse outcome pathway descriptions can be found at aopwiki.org. This dataset is not publicly accessible because: This product is a workshop report. There are no data associated with this product. It can be accessed through the following means: AOP descriptions that illustrate concepts discussed in this paper can be accessed via aopwiki.org. Format: There are no data associated with this product. This dataset is associated with the following publication: Villeneuve, D., B. Landesmann, P. Allavena, N. Ashley, A. Bal-Price, E. Corsini, S. Halappanavar, T. Hussell, D. Laskin, T. Lawrence, D. Nikolic-Paterson, M. Pallardy, A. Paini, R. Pieters, R. Roth, and F. Tschudi-Monnet. Representing the process of inflammation as key events in adverse outcome pathways. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 163(2): 346-352, (2018).

A set of three proposed "hub" key events were used to link together a series of example adverse outcome pathway (AOP) descriptions that were previously not linked in an AOP network. While there are no data associated with this product, the relevant adverse outcome pathway descriptions can be found at aopwiki.org. This dataset is not publicly accessible because: This product is a workshop report. There are no data associated with this product. It can be accessed through the following means: AOP descriptions that illustrate concepts discussed in this paper can be accessed via aopwiki.org. Format: There are no data associated with this product. This dataset is associated with the following publication: Villeneuve, D., B. Landesmann, P. Allavena, N. Ashley, A. Bal-Price, E. Corsini, S. Halappanavar, T. Hussell, D. Laskin, T. Lawrence, D. Nikolic-Paterson, M. Pallardy, A. Paini, R. Pieters, R. Roth, and F. Tschudi-Monnet. Representing the process of inflammation as key events in adverse outcome pathways. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 163(2): 346-352, (2018).

In September, 2015, a water sample was collected downstream of a major metropolitan waste water treatment plant that discharges to the South Platte River, Colorado, USA. The grab sample, 1L, was collected just below the water surface, directly into a pre-cleaned, organic-free, amber glass bottle. The water sample was extracted by solid phase extraction using an Oasis-HLB glass catridge. Cartidges were conditioned sequentially using 5mL each of ethyl acetate, 50:50 methanol (MeOH):dichloromethane (DCM), MeOH, and water. The extract in DMSO was tested in the Attagene cis- and trans-FactorialTM assays (http://www.attagene.com/technology.php; Martin and others 2010; Romanov and others 2008). Data were analyzed using an established analysis pipeline for analyzing ToxCast™ high throughput screening data (Filer and others 2017). "Active hits" in the Attagene assay are included in the data table. This dataset is associated with the following publication: Knapen, D., M. Angrish, M. Fortin, I. Katsiadaki, M. Leonard, L. Mariotta-Casaluci, S. Munn, J. O'Brien, N. Pollesch, L.C. Smith, X. Zhang, and D. Villeneuve. Adverse outcome pathway networks I: Development and applications. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(6): 1723-1733, (2018).

In September, 2015, a water sample was collected downstream of a major metropolitan waste water treatment plant that discharges to the South Platte River, Colorado, USA. The grab sample, 1L, was collected just below the water surface, directly into a pre-cleaned, organic-free, amber glass bottle. The water sample was extracted by solid phase extraction using an Oasis-HLB glass catridge. Cartidges were conditioned sequentially using 5mL each of ethyl acetate, 50:50 methanol (MeOH):dichloromethane (DCM), MeOH, and water. The extract in DMSO was tested in the Attagene cis- and trans-FactorialTM assays (http://www.attagene.com/technology.php; Martin and others 2010; Romanov and others 2008). Data were analyzed using an established analysis pipeline for analyzing ToxCast™ high throughput screening data (Filer and others 2017). "Active hits" in the Attagene assay are included in the data table. This dataset is associated with the following publication: Knapen, D., M. Angrish, M. Fortin, I. Katsiadaki, M. Leonard, L. Mariotta-Casaluci, S. Munn, J. O'Brien, N. Pollesch, L.C. Smith, X. Zhang, and D. Villeneuve. Adverse outcome pathway networks I: Development and applications. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(6): 1723-1733, (2018).

No novel data were reported in association with this product. This dataset is not publicly accessible because: The associated publication is a review/forum-type article. No novel scientific data are reported. All data cited have been previously published elsewhere. It can be accessed through the following means: Not applicable. Format: This article is a review/forum-type article. No novel scientific data are included. This dataset is associated with the following publication: Knapen, D., E. Stinckens, J. Cavallin, G. Ankley, H. Holbech, D. Villeneuve, and L. Vergauwen. Toward an AOP network-based tiered testing strategy for the assessment of thyroid hormone disruption. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 54(16): 8491-8499, (2020).

No novel data were reported in association with this product. This dataset is not publicly accessible because: The associated publication is a review/forum-type article. No novel scientific data are reported. All data cited have been previously published elsewhere. It can be accessed through the following means: Not applicable. Format: This article is a review/forum-type article. No novel scientific data are included. This dataset is associated with the following publication: Knapen, D., E. Stinckens, J. Cavallin, G. Ankley, H. Holbech, D. Villeneuve, and L. Vergauwen. Toward an AOP network-based tiered testing strategy for the assessment of thyroid hormone disruption. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 54(16): 8491-8499, (2020).

This research was designed to evaluate whether a biologically-based computational model aligned with an adverse outcome pathway (AOP) could effectively predict animal (in vivo) responses to chemicals shown to inhibit the enzyme aromatase in a non-animal (in vitro) screening assays. Aromatase is an enzyme that plays a critical role in the synthesis of estrogens, an important class of hormones, and chemicals that inhibit aromatase are viewed as probable endocrine disrupting compounds. Although the model was not able to accurately predict the average in vivo responses observed for all chemicals tested, there was strong qualitative to semi-quantitative agreement with the proposed AOP and predictions did fall within the distribution of measured values. Consequently, this “new approach methodology” likely has utility for screening-level assessments. This work helps to establish the confidence and limitations of this approach. The data set includes: 1) High throughput screening results for chemicals identified as aromatase inhibitors. 2) Novel in vitro aromatase inhibition data for six chemicals. 3) Modeled predictions of impacts on 17b-estradiol and vitellogenin concentrations over a range of concentrations. 4) Measured biological effects of 3 aromatase inhibitors in fathead minnows exposed for 24 h. 5) Measured plasma and water concentrations of the test chemicals. This dataset is associated with the following publication: Villeneuve, D., B. Blackwell, J. Cavallin, W. Cheng, R. Conolly, D. Feifarek, K. Jensen, M. Kahl, R. Milsk, S. Poole, E. Randolph, T. Saari, and G. Ankley. Case study in 21st century ecotoxicology: Using in vitro aromatase inhibition data to predict short term in vivo responses in adult female fish. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 40(4): 1155-1170, (2021).