A scalable approach to absolute quantitation in metabolomics
Luke S. Ferro, Alan Y. L. Wong, Jack Howland, Ana S.H. Costa, Jefferson G. Pruyne, Devesh Shah, Joshua D. Lauterbach, Steven B. Hooper, Mimoun Cadosh Delmar, Jack Geremia, Timothy Kassis, Naama Kanarek, Jennifer M. Campbell
This paper introduces Pyxis, a machine learning tool for absolute metabolite quantification in metabolomics, demonstrating its scalability and efficiency compared to traditional methods.
bioRxiv · Sep 9, 2024 · PreprintSystems Biology