Machine Learning: New Ideas and Tools in Environmental Science and Engineering

Shifa Zhong, Kai Zhang, Majid Bagheri, +16

Environmental Science & Technology

Artificial IntelligenceEngineeringMachine LearningComputer AnalysisMachine Learning Tool +18

Structures of Endocrine-Disrupting Chemicals Determine Binding to and Activation of the Estrogen Receptor α and Androgen Receptor

Haoyue Tan, Xiaoxiang Wang, Huixiao Hong, +7

Environmental Science & Technology

Structures of Endocrine-Disrupting Chemicals Correlate with the Activation of 12 Classic Nuclear Receptors

Haoyue Tan, Qinchang Chen, Huixiao Hong, +5

Environmental Science & Technology

Classic Nuclear ReceptorsMedicinal ChemistryCompound NrCell SignalingMolecular Physiology +17

Are New Phthalate Ester Substitutes Safer than Traditional DBP and DiBP? Comparative Endocrine-Disrupting Analyses on Zebrafish Using <i>In Vivo</i>, Transcriptome, and <i>In Silico</i> Approaches

Haoyue Tan, Pan Gao, Yiwen Luo, +9

Environmental Science & Technology

Development, Validation, and Application of a Human Reproductive Toxicity Prediction Model Based on Adverse Outcome Pathway

Haoyue Tan, Jinqiu Wu, Rong Zhang, +6

Environmental Science & Technology

Molecular Initiating Events of Bisphenols on Androgen Receptor-Mediated Pathways Provide Guidelines for <i>in Silico</i> Screening and Design of Substitute Compounds

Qinchang Chen, Xiaoxiang Wang, Haoyue Tan, +5

Environmental Science & Technology Letters

Androgen ReceptorSubstitute CompoundsPharmacotherapyChemical BiologySystems Pharmacology +17

Identify organic contaminants of high-concern based on non-targeted toxicity testing and non-targeted LC-HRMS analysis in tap water and source water along the Yangtze River

Shaoqing Zhang, Liben Chou, Wenxuan Zhu, +13

Water Research

Environmental ChemistrySource WaterEngineeringEmerging ContaminantWater Contamination +10

A novel molecular pathway of lipid accumulation in human hepatocytes caused by PFOA and PFOS

Xiao Gou, Yan Lu, Pu Xia, +5

Environment International

Deep Learning in Environmental Toxicology: Current Progress and Open Challenges

Haoyue Tan, Jinsha Jin, Chao Fang, +5

ACS ES&T Water

Convolutional Neural NetworkEngineeringMachine LearningNeural NetworkAutoencoders +17