Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385406507> ?p ?o ?g. }
- W4385406507 abstract "Covering: up to March 2023Machine learning (ML) has emerged as a popular tool for analyzing the structures of natural products (NPs). This review presents a summary of the recent advancements in ML-assisted mass spectrometry (MS) and nuclear magnetic resonance (NMR) data analysis to establish the chemical structures of NPs. First, ML-based MS/MS analyses that rely on library matching are discussed, which involves the utilization of ML algorithms to calculate similarity, predict the MS/MS fragments, and form molecular fingerprint. Then, ML assisted MS/MS structural annotation without library matching is reviewed. Furthermore, the cases of ML algorithms in assisting structural studies of NPs based on NMR are discussed from four perspectives: NMR prediction, functional group identification, structural categorization and quantum chemical calculation. Finally, the review concludes with a discussion of the challenges and the trends associated with the structural establishment of NPs based on ML algorithms." @default.
- W4385406507 created "2023-08-01" @default.
- W4385406507 creator A5000734034 @default.
- W4385406507 creator A5014518747 @default.
- W4385406507 date "2023-01-01" @default.
- W4385406507 modified "2023-09-28" @default.
- W4385406507 title "Machine learning-assisted structure annotation of natural products based on MS and NMR data" @default.
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