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Showing 1–4 of 4 results
Advanced filters: Author: Xavier Domingo-Almenara Clear advanced filters

  • The use of machine learning for identifying small molecules through their retention time’s predictions has been challenging so far. Here the authors combine a large database of liquid chromatography retention time with a deep learning approach to enable accurate metabolites’s identification.

    • Xavier Domingo-Almenara
    • Carlos Guijas
    • Gary Siuzdak
    ResearchOpen Access
    Nature Communications
    Volume: 10, P: 1-9

  • Kidney metabolism in disease is important but not well understood. Here, using isotope-guided metabolomics, the authors show that lysine’s metabolic activity conveys kidney protection in hypertension through accelerated metabolism and physiological effects on tubular function.

    • Markus M. Rinschen
    • Oleg Palygin
    • Alexander Staruschenko
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-17

  • This protocol describes how to use natural language processing software to analyze metabolomics data to prioritize metabolites for further study, identify candidates for unique disease biomarkers and elucidate their function on a pathway level.

    • Erica L.-W. Majumder
    • Elizabeth M. Billings
    • Gary Siuzdak
    Protocols
    Nature Protocols
    Volume: 16, P: 1376-1418