Εξειδίκευση τύπου :	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	Automated metabolite identification from biological fluid 1H NMR spectra
Δημιουργός/Συγγραφέας:	Filntisi A. Fotakis C. Asvestas P. Matsopoulos G.K. [EL] Ζουμπουλάκης, Παναγιώτης[EN] Zoumpoulakis, Panagiotis Cavouras D.
Εκδότης:	Springer New York LLC
Ημερομηνία:	2017
Γλώσσα:	Αγγλικά
ISSN:	1573-3882
DOI:	10.1007/s11306-017-1286-8
Περίληψη:	Introduction: Metabolite identification in biological samples using Nuclear Magnetic Resonance (NMR) spectra is a challenging task due to the complexity of the biological matrices. Objectives: This paper introduces a new, automated computational scheme for the identification of metabolites in 1D 1H NMR spectra based on the Human Metabolome Database. Methods: The methodological scheme comprises of the sequential application of preprocessing, data reduction, metabolite screening and combination selection. Results: The proposed scheme has been tested on the 1D 1H NMR spectra of: (a) an amino acid mixture, (b) a serum sample spiked with the amino acid mixture, (c) 20 blood serum, (d) 20 human amniotic fluid samples, (e) 160 serum samples from publicly available database. The methodological scheme was compared against widely used software tools, exhibiting good performance in terms of correct assignment of the metabolites. Conclusions: This new robust scheme accomplishes to automatically identify peak resonances in 1H-NMR spectra with high accuracy and less human intervention with a wide range of applications in metabolic profiling.
Τίτλος πηγής δημοσίευσης:	Metabolomics
Τόμος/Κεφάλαιο:	13
Τεύχος:	12
Θεματική Κατηγορία:	[EL] Φαρμακευτική χημεία[EN] Pharmaceutical chemistry [EL] Βιοχημεία[EN] Biochemistry
Λέξεις-Κλειδιά:	1H NMR spectroscopy Automated metabolite identification Human Metabolome Database Metabolomics Spectra preprocessing
Αξιολόγηση από ομότιμους (peer reviewed):	Ναι
Κάτοχος πνευματικών δικαιωμάτων:	© 2017, Springer Science+Business Media, LLC.
Σημειώσεις:	State Scholarships Foundation, IKY. This work was funded by a State Scholarships Foundation (IKY) Fellowship of Excellence for postgraduate studies in Greece—Siemens Program.
Εμφανίζεται στις συλλογές:	Ινστιτούτο Χημικής Βιολογίας - Επιστημονικό έργο