Research Articles
Multi-Sorbent Extraction Strategies for Broad-Spectrum Contaminant Analysis in Complex Matrices
This article provides a comprehensive overview of multi-sorbent extraction strategies, a powerful approach for the broad-spectrum analysis of contaminants in complex biological and environmental samples.
Ensemble Machine Learning for Spatiotemporal Analysis of Environmental Contaminants: From Fundamentals to Advanced Applications
This comprehensive review explores the transformative potential of ensemble machine learning models in analyzing spatiotemporal trends of environmental contaminants.
Chemical Fingerprinting and Pattern Recognition: Advanced Source Tracking from Drug Discovery to Clinical Applications
This article explores the transformative role of chemical fingerprinting and pattern recognition technologies in biomedical research and drug development.
Machine Learning-Powered Non-Target Analysis: A Systematic Framework for Contaminant Source Identification
This article provides a comprehensive review of the integration of Machine Learning (ML) with High-Resolution Mass Spectrometry (HRMS)-based Non-Target Analysis (NTA) for the critical task of contaminant source identification.
HRMS Retention Time Correction and Alignment: A Comprehensive Guide for Reliable Metabolomics and Proteomics Data
This article provides a comprehensive overview of retention time (RT) correction and alignment for Liquid Chromatography-High-Resolution Mass Spectrometry (LC-HRMS) data, a critical preprocessing step in untargeted metabolomics and proteomics.
Advancing Environmental Hazard Assessment: A Comprehensive Guide to QSAR Model Development and Validation
This article provides researchers, scientists, and drug development professionals with a comprehensive overview of Quantitative Structure-Activity Relationship (QSAR) model development for environmental chemical hazard assessment.
Dimensionality Reduction for Environmental Chemical Data: Techniques, Applications, and Best Practices for Researchers
This article provides a comprehensive guide to dimensionality reduction techniques (DRTs) for researchers and professionals analyzing high-dimensional environmental chemical datasets.
Machine Learning for Chemical Life Cycle Assessment: Predicting Toxicity and Environmental Impacts
This article explores the integration of machine learning (ML) with Life Cycle Assessment (LCA) to address critical data gaps in chemical toxicity and environmental impact evaluation.
Integrating Mechanistic Data: The Adverse Outcome Pathway Framework in Modern Toxicology
This article explores the Adverse Outcome Pathway (AOP) framework, a transformative approach for organizing mechanistic toxicological data to enhance chemical safety assessment and drug development.
Impact Outcome Pathways (IOP): A Next-Generation Framework for Safe and Sustainable Drug Development
This article explores the transformative potential of the Impact Outcome Pathway (IOP) framework for integrating safety and sustainability into pharmaceutical research and development.