Sakda Khoomrung
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Biography and Research Information
OverviewAI-generated summary
Sakda Khoomrung's research focuses on the application of computational methods, particularly deep learning, to analyze complex biological data, with a significant emphasis on metabolomics. His work explores how these advanced analytical techniques can be integrated with genomic and proteomic data to advance precision medicine.
Khoomrung has investigated the use of Saccharomyces cerevisiae as a model organism for metabolic engineering, particularly for the production of biofuels and valuable compounds like L-ornithine. His research has also delved into understanding lipid metabolism and acid tolerance in yeast, utilizing techniques such as gas chromatography-mass spectrometry and high-performance liquid chromatography with charged aerosol detection. His publications include work on the functional expression of wax ester synthases and the rewiring of metabolic pathways in yeast.
With an h-index of 23 and over 2,171 citations from 75 publications, Khoomrung is recognized as a highly cited researcher. He has collaborated with several colleagues at the University of Arkansas for Medical Sciences, including Alongkorn Kurilung, Intawat Nookaew, Thidathip Wongsurawat, and Piroon Jenjaroenpun. Khoomrung maintains an active laboratory website.
Metrics
- h-index: 23
- Publications: 75
- Citations: 2,171
Selected Publications
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LC-QTOF-MS <sup>E</sup> with MS <sup>1</sup> -based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis (2025)
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- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
- LC-QTOF-MSE with MS1-based precursor ion quantification and SiMD-assisted identification enhances human urine metabolite analysis
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