Key research themes
1. What are the methodological challenges and strategies for ensuring data quality and reproducibility in untargeted metabolomics?
This research area focuses on tackling the inherent analytical and computational challenges in untargeted metabolomics workflows, with an emphasis on quality assurance (QA), quality control (QC), data pre-processing, and standardization of protocols to produce reproducible and reliable metabolomic data. The theme is critical because untargeted metabolomics generates complex, high-dimensional datasets prone to measurement variability, identification ambiguity, and batch effects, complicating biological interpretation and cross-study comparisons.
2. How do analytical technologies like LC-MS and GC-MS, including emerging ambient mass spectrometry techniques, advance metabolomic profiling and what are their comparative strengths and limitations?
This theme investigates the state-of-the-art in analytical instrumentation for metabolomics, focusing on liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), and emerging ambient mass spectrometry (AMS) approaches. Research examines their capabilities for comprehensive metabolite detection, challenges in sample preparation, ionization, quantification, and throughput, and compares their suitability across metabolite classes and biological contexts.
3. How is metabolomics applied to biomarker discovery and clinical research across diverse fields including disease diagnostics, nutrition, and food safety?
This theme encompasses the translational utilization of metabolomics in identifying biomarkers for disease diagnostics, monitoring therapeutic intervention, precision nutrition, and ensuring food quality and safety. It focuses on methodological pipelines from sample acquisition to data interpretation and integration with other omics while addressing challenges in biological variability, metabolite annotation, and practical implementation for robust biomarker applications.