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@article{Takis:2018:10.1016/j.trac.2018.10.036,
author = {Takis, PG and Ghini, V and Tenori, L and Turano, P and Luchinat, C},
doi = {10.1016/j.trac.2018.10.036},
journal = {TrAC - Trends in Analytical Chemistry},
title = {Uniqueness of the NMR approach to metabolomics},
url = {http://dx.doi.org/10.1016/j.trac.2018.10.036},
year = {2018}
}

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TY  - JOUR
AB  - © 2018 Elsevier B.V. NMR measures a relatively small portion of the human metabolome, which roughly corresponds to all free small molecules present in concentrations ≥1 μM. However, the method is intrinsically quantitative and highly reproducible and, whenever standardized pre-analytical and analytical procedures are used, it allows for fast fingerprinting and profiling of a variety of biosamples. While developing methods for accurate and automated identification and quantitation of detectable metabolites, we have proposed a Urine Shift Predictor that also provides the concentration of NMR-invisible inorganic ions. For biomedical applications, two peculiar features are associated to the fast, untargeted NMR-metabolomic fingerprinting of biofluids, i.e. the ability to: i) identify the individual phenotype that constitutes the metabolic signature of a person and monitor its behavior over time; ii) identify the signature of different diseases. The combination of the two in longitudinal cohort studies could become a tool for fast and untargeted screening of populations.
AU  - Takis,PG
AU  - Ghini,V
AU  - Tenori,L
AU  - Turano,P
AU  - Luchinat,C
DO  - 10.1016/j.trac.2018.10.036
PY  - 2018///
SN  - 0165-9936
TI  - Uniqueness of the NMR approach to metabolomics
T2  - TrAC - Trends in Analytical Chemistry
UR  - http://dx.doi.org/10.1016/j.trac.2018.10.036
ER  -

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