Dataset used in ORD-035008 - A Set of Six Gene Expression Biomarkers and Their Thresholds Identify Rat Liver Tumorigens in Short-Term Assays

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The links provided include the DrugMatrix-Affymetrix study, the TG-GATES study, and the TempO-Seq S1500+ study. This dataset is associated with the following publication: Lewis, R., T. Hill III, and C. Corton. A set of six Gene expression biomarkers and their thresholds identify rat liver tumorigens in short-term assays. TOXICOLOGY. Elsevier Science Ltd, New York, NY, USA, 443: 152547, (2020).

Dataset for ORD-033344: A Set of Six Gene Expression Biomarkers Identify Rat Liver Tumorigens in Short-Term Assays

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Microarray experiments used in the study. This dataset is associated with the following publication: Corton, J., T. Hill, J. Sutherland, J. Stevens, and J. Rooney. A Set of Six Gene Expression Biomarkers Identify Rat Liver Tumorigens in Short-Term Assays. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 177(1): 11-26, (2020).

Dataset for ORD-033373: Gene Expression Thresholds Are Predictive of Rat Liver Tumorigens in Short-Term Assays

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The microarray experiments used in the study. This dataset is associated with the following publication: Hill, T., J. Rooney, J. Abedini, H. El-Masri, C. Wood, and J. Corton. Gene Expression Thresholds Derived From Short-term Exposures Identify Rat Liver Tumorigens. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 177(1): 41-59, (2020).

Dataset for ORD-033294: Mining a human transcriptome database for chemical modulators of NRF2

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Gene Expression Omnibus and ArrayExpress archived study numbers of microarray data used in the study. This dataset is associated with the following publication: Rooney, J., B. Chorley, S. Hiemstra, S. Wink, X. Wang, D. Bell, B. van de Water, and J. Corton. Mining a human transcriptome database for chemical modulators of Nrf2 (PLOS ONE). PLoS ONE. Public Library of Science, San Francisco, CA, USA, 15(9): e0239367, (2020).

Dataset for ORD-037038: Constitutive expression of human CYPs

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The raw values used to create figures 1 and 2 and table 3. This dataset is associated with the following publication: Liu, J., Y. Lu, C. Corton, and C. Klaassen. Expression of cytochrome P450 isozyme transcripts and activities in human livers. XENOBIOTICA. Taylor & Francis, Inc., Philadelphia, PA, USA, 51(3): 279-286, (2021).

Datasets used in ORD-023413: Frequent Modulation of the Sterol Regulatory Element Binding Protein (SREBP) by Chemical Exposure in the Livers of Rats

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Datasets used in ORD-023413: Frequent Modulation of the Sterol Regulatory Element Binding Protein (SREBP) by Chemical Exposure in the Livers of Rats. This dataset is associated with the following publication: Corton, C. Frequent modulation of the sterol regulatory element binding protein (SREBP) by chemical exposure in the livers of rats. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 10: 113-129, (2019).

ORD-037657: Sex-, age-, race-, and disease-dependent variations in NRF2-regulated genes in human livers

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Data was generated at KUMC, not EPA. There is no EPA data that is part of this submission. This dataset is associated with the following publication: Liu, J., J.Y. Cui, Y. Lu, C. Corton, and C. Klaassen. Sex-, Age-, and Race/Ethnicity-Dependent Variations in Drug-Processing and NRF2-Regulated Genes in Human Livers. DRUG METABOLISM AND DISPOSITION. American Society for Pharmacology and Experimental Therapeutics, Bethesda, MD, USA, 49(1): 111-119, (2021).

Dataset for ORD-040059: Identification of Chemical Modulators of NF-κB Using a Gene Expression Biomarker Approach

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Dataset used in ORD-040059: Identification of Chemical Modulators of NF-κB Using a Gene Expression Biomarker Approach that includes publicaly available microarray datasets. This dataset is associated with the following publication: Korunes, K., J. Liu, R. Huang, M. Xia, K. Houck, and C. Corton. A gene expression biomarker for predictive toxicology to identify chemical modulators of NF-κB. PLOS ONE. Public Library of Science, San Francisco, CA, USA, 17(2): e0261854, (2022).

NIHMS1933008-supplement-Supplementary data 1 (1)

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This ScienceHub entry provides Associated Data (Supplementary data 1) from the published manuscript Comput Toxicol. 2023 Jan 25;25:100261. doi: 10.1016/j.comtox.2023.100261. Further availability of data, as stated in the manuscript, will be made available on request. This dataset is associated with the following publication: Romano, J., L. Mei, J. Senn, J. Moore, and H. Mortensen. Exploring genetic influences on adverse outcome pathways using heuristic simulation and graph data science. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 25: 100261, (2023).

Datasets used in ORD-023408: A Gene Expression Biomarker Identifies Chemicals and Other Factors That Modulate Sterol Regulatory Element Binding Protein (SREBP) Highlighting Differences in Targeted Regulation of Cholesterogenic and Lipogenic Genes

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Datasets used in ORD-023408: A Gene Expression Biomarker Identifies Chemicals and Other Factors That Modulate Sterol Regulatory Element Binding Protein (SREBP) Highlighting Differences in Targeted Regulation of Cholesterogenic and Lipogenic Genes. This dataset is associated with the following publication: Rooney, J., B. Chorley, and C. Corton. A gene expression biomarker identifies factors that modulate sterol regulatory element binding protein. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 10: 63-77, (2019).