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Determination of Flavonoid Glycoside Isomers Using Vision Transformer and Tandem Mass Spectrometry
- Park, Ji In;
- Kim, Myeong Ji;
- Lee, Kyu Hyeong;
- Oh, Seung Hyun;
- Kang, Young Hoon;
- ... Kim, Hyunwoo
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1초록
A vision transformer (ViT)-based deep neural network was applied to classify the flavonoid glycoside isomers by analyzing electrospray ionization tandem mass spectrometry (ESI-MS/MS) spectra. Our model successfully classified the flavonoid isomers with various substitution patterns (3-O, 6-C, 7-O, 8-C, 4 '-O) and multiple glycosides, achieving over 80% accuracy during training. In addition, the experimental spectra from flavonoid glycoside standards were acquired with different adducts, and our model showed robust performance regardless of the experimental conditions. As a result, the vision transformer-based computer vision model is promising for analyzing mass spectrometry data.
키워드
flavonoid; artificial intelligence; vision transformer; DIFFERENTIATION
- 제목
- Determination of Flavonoid Glycoside Isomers Using Vision Transformer and Tandem Mass Spectrometry
- 저자
- Park, Ji In; Kim, Myeong Ji; Lee, Kyu Hyeong; Oh, Seung Hyun; Kang, Young Hoon; Kim, Hyunwoo
- 발행일
- 2024-12
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- Article
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