Articles producció científicaEnginyeria Electrònica, Elèctrica i Automàtica

Metabolite discovery: Biochemistry's scientific driver

  • Datos identificativos

    Identificador:  imarina:9242580
    Autores:  Giera, Martin; Yanes, Oscar; Siuzdak, Gary
    Resumen:
    Metabolite identification represents a major challenge, and opportunity, for biochemistry. The collective characterization and quantification of metabolites in living organisms, with its many successes, represents a major biochemical knowledgebase and the foundation of metabolism's rebirth in the 21st century; yet, characterizing newly observed metabolites has been an enduring obstacle. Crystallography and NMR spectroscopy have been of extraordinary importance, although their applicability in resolving metabolism's fine structure has been restricted by their intrinsic requirement of sufficient and sufficiently pure materials. Mass spectrometry has been a key technology, especially when coupled with high-performance separation technologies and emerging informatic and database solutions. Even more so, the collective of artificial intelligence technologies are rapidly evolving to help solve the metabolite characterization conundrum. This perspective describes this challenge, how it was historically addressed, and how metabolomics is evolving to address it today and in the future.Copyright © 2021. Published by Elsevier Inc.
  • Otros:

    Enlace a la fuente original: https://www.sciencedirect.com/science/article/abs/pii/S1550413121005337
    Referencia de l'ítem segons les normes APA: Giera, Martin; Yanes, Oscar; Siuzdak, Gary (2022). Metabolite discovery: Biochemistry's scientific driver. Cell Metabolism, 34(1), 21-34. DOI: 10.1016/j.cmet.2021.11.005
    Referencia al articulo segun fuente origial: Cell Metabolism. 34 (1): 21-34
    DOI del artículo: 10.1016/j.cmet.2021.11.005
    Año de publicación de la revista: 2022
    Entidad: Universitat Rovira i Virgili
    Versión del articulo depositado: info:eu-repo/semantics/submittedVersion
    Fecha de alta del registro: 2024-10-12
    Autor/es de la URV: Yanes Torrado, Óscar
    Departamento: Enginyeria Electrònica, Elèctrica i Automàtica
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Tipo de publicación: Journal Publications
    Autor según el artículo: Giera, Martin; Yanes, Oscar; Siuzdak, Gary
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Áreas temáticas: Physiology, Odontología, Molecular biology, Medicina ii, Medicina i, Interdisciplinar, General medicine, Endocrinology & metabolism, Educação física, Ciências biológicas ii, Ciências biológicas i, Cell biology
    Direcció de correo del autor: oscar.yanes@urv.cat
  • Palabras clave:

    Unknowns
    Structure
    Nuclear magnetic resonance
    Metabolites
    Mass-spectrometry data
    Mass spectrometry
    Biochemistry
    Artificial intelligence
    platform
    nmr-spectroscopy
    metabolomics
    induced dissociation
    identification
    deconvolution
    computational tool
    chromatography
    acids
    Cell Biology
    Endocrinology & Metabolism
    Molecular Biology
    Physiology
    Odontología
    Medicina ii
    Medicina i
    Interdisciplinar
    General medicine
    Educação física
    Ciências biológicas ii
    Ciências biológicas i
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