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A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.
Dona, Anthony C; Kyriakides, Michael; Scott, Flora; Shephard, Elizabeth A; Varshavi, Dorsa; Veselkov, Kirill; Everett, Jeremy R.
Afiliação
  • Dona AC; Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, SW7 2AZ, United Kingdom.
  • Kyriakides M; Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, SW7 2AZ, United Kingdom.
  • Scott F; Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, United Kingdom.
  • Shephard EA; Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, United Kingdom.
  • Varshavi D; Medway Metabonomics Research Group, University of Greenwich, Chatham Maritime, Kent ME4 4TB, United Kingdom.
  • Veselkov K; Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, SW7 2AZ, United Kingdom.
  • Everett JR; Medway Metabonomics Research Group, University of Greenwich, Chatham Maritime, Kent ME4 4TB, United Kingdom.
Comput Struct Biotechnol J ; 14: 135-53, 2016.
Article em En | MEDLINE | ID: mdl-27087910
Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.
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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Comput Struct Biotechnol J Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Reino Unido