Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach
Por um escritor misterioso
Last updated 29 março 2025
Full article: Bringing together scientific disciplines for collaborative undertakings: a vision for advancing the adverse outcome pathway framework

Frontiers From Causal Networks to Adverse Outcome Pathways: A Developmental Neurotoxicity Case Study

Identification of toxicity pathway of diesel particulate matter using AOP of PPARγ inactivation leading to pulmonary fibrosis - ScienceDirect

High throughput data-based, toxicity pathway-oriented development of a quantitative adverse outcome pathway network linking AHR activation to lung damages - ScienceDirect

High throughput data-based, toxicity pathway-oriented development of a quantitative adverse outcome pathway network linking AHR activation to lung damages - ScienceDirect
GitHub - UOSEST/Jeong-et-al-2019-CRT-ToxCast-AOP206

Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach

Frontiers A Case Study on Integrating a New Key Event Into an Existing Adverse Outcome Pathway on Oxidative DNA Damage: Challenges and Approaches in a Data-Rich Area

Toxics, Free Full-Text

Jaeseong JEONG, PostDoc Position, Doctor of Philosophy, University of Seoul, Seoul, School of Environmental Engineering
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