Our research involves applying mass spectrometry-based technologies to perform molecular phenotyping at the population level. This work entails the development of both LC/MS and GC/MS methods for the quantification of lipids and other metabolites. A major focus of the lab also centers on developing the associated bioinformatics approaches including pathway analysis and network construction as well as multivariate statistical methods for integration of 'omics-based data structures.
- Comparison of Metabolites Variation and Antiobesity Effects of Fermented versus Nonfermented Mixtures of Cudrania tricuspidata, Lonicera caerulea, and Soybean According to Fermentation In Vitro and In Vivo.
- Global Metabolic Responses to Salt Stress in Fifteen Species.
- Human plasma metabolomics for identifying differential metabolites and predicting molecular subtypes of breast cancer.
- GC-MS metabolic profiling of Cabernet Sauvignon and Merlot cultivars during grapevine berry development and network analysis reveals a stage- and cultivar-dependent connectivity of primary metabolites.
- Multi-platform metabolomics analyses of a broad collection of fragrant and non-fragrant rice varieties reveals the high complexity of grain quality characteristics.
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