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Environmental and Molecular Mutagenesis
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September 12, 2025
Identifying Gene Predictors of Chemicals Linked With Breast Cancer: A Machine Learning Analysis of MCF7 Cellular Transcriptomic Screening Data
Lauren E Koval, Richard Judson, Julia E Rager
Journal of Exposure Science & Environmental Epidemiology
|
June 16, 2022
Environmental mixtures and breast cancer: identifying co-exposure patterns between understudied vs breast cancer-associated chemicals using chemical inventory informatics
Lauren E Koval, Kathie L Dionisio, Katie Paul Friedman, et al.
Toxics
|
May 27, 2022
Chemical Mixtures in Household Environments: In Silico Predictions and In Vitro Testing of Potential Joint Action on PPARγ in Human Liver Cells
Celeste K Carberry, Toby Turla, Lauren E Koval, et al.
Metabolites
|
October 28, 2025
Development of LC-MS/MS Database Based on 250 Potentially Highly Neuroactive Compounds and Their Metabolites
Taylor Teitelbaum, Haoduo Zhao, Lauren E Koval, et al.
Environmental Science & Technology
|
November 18, 2022
Wildfire Variable Toxicity: Identifying Biomass Smoke Exposure Groupings through Transcriptomic Similarity Scoring
Lauren E Koval, Celeste K Carberry, Yong Ho Kim, et al.
Journal of Exposure Science & Environmental Epidemiology
|
November 21, 2025
Environmental factors influencing hormone receptor positive breast cancer incidence: integrating chemical signatures from dust wipes with self-reported sources of exposure
Lauren E Koval, Yun-Chung Hsiao, Ellie Jiang, et al.
Computational Toxicology (Amsterdam, Netherlands)
|
May 20, 2021
Predictive modeling of biological responses in the rat liver using <i>in vitro</i> Tox21 bioactivity: Benefits from high-throughput toxicokinetics
Caroline Ring, Nisha S Sipes, Jui-Hua Hsieh, et al.
Environmental Research
|
December 5, 2024
The environmental neuroactive chemicals list of prioritized substances for human biomonitoring and neurotoxicity testing: A database and high-throughput toxicokinetics approach
Julia E Rager, Lauren E Koval, Elise Hickman, et al.
Environment International
|
July 21, 2022
Wildfires and extracellular vesicles: Exosomal MicroRNAs as mediators of cross-tissue cardiopulmonary responses to biomass smoke
Celeste K Carberry, Lauren E Koval, Alexis Payton, et al.
Frontiers in Toxicology
|
July 11, 2022
Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research
Kyle Roell, Lauren E Koval, Rebecca Boyles, et al.
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Search research articles
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Showing results (1-10 of 12) with videos related to
Sort By:
Page
of 2
Environmental and Molecular Mutagenesis
|
September 12, 2025
Identifying Gene Predictors of Chemicals Linked With Breast Cancer: A Machine Learning Analysis of MCF7 Cellular Transcriptomic Screening Data
Lauren E Koval, Richard Judson, Julia E Rager
Journal of Exposure Science & Environmental Epidemiology
|
June 16, 2022
Environmental mixtures and breast cancer: identifying co-exposure patterns between understudied vs breast cancer-associated chemicals using chemical inventory informatics
Lauren E Koval, Kathie L Dionisio, Katie Paul Friedman, et al.
Toxics
|
May 27, 2022
Chemical Mixtures in Household Environments: In Silico Predictions and In Vitro Testing of Potential Joint Action on PPARγ in Human Liver Cells
Celeste K Carberry, Toby Turla, Lauren E Koval, et al.
Metabolites
|
October 28, 2025
Development of LC-MS/MS Database Based on 250 Potentially Highly Neuroactive Compounds and Their Metabolites
Taylor Teitelbaum, Haoduo Zhao, Lauren E Koval, et al.
Environmental Science & Technology
|
November 18, 2022
Wildfire Variable Toxicity: Identifying Biomass Smoke Exposure Groupings through Transcriptomic Similarity Scoring
Lauren E Koval, Celeste K Carberry, Yong Ho Kim, et al.
Journal of Exposure Science & Environmental Epidemiology
|
November 21, 2025
Environmental factors influencing hormone receptor positive breast cancer incidence: integrating chemical signatures from dust wipes with self-reported sources of exposure
Lauren E Koval, Yun-Chung Hsiao, Ellie Jiang, et al.
Computational Toxicology (Amsterdam, Netherlands)
|
May 20, 2021
Predictive modeling of biological responses in the rat liver using <i>in vitro</i> Tox21 bioactivity: Benefits from high-throughput toxicokinetics
Caroline Ring, Nisha S Sipes, Jui-Hua Hsieh, et al.
Environmental Research
|
December 5, 2024
The environmental neuroactive chemicals list of prioritized substances for human biomonitoring and neurotoxicity testing: A database and high-throughput toxicokinetics approach
Julia E Rager, Lauren E Koval, Elise Hickman, et al.
Environment International
|
July 21, 2022
Wildfires and extracellular vesicles: Exosomal MicroRNAs as mediators of cross-tissue cardiopulmonary responses to biomass smoke
Celeste K Carberry, Lauren E Koval, Alexis Payton, et al.
Frontiers in Toxicology
|
July 11, 2022
Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research
Kyle Roell, Lauren E Koval, Rebecca Boyles, et al.
Page
of 2