Variable selection using iterative reformulation of training set models for discrimination of samples: application to gas chromatography/mass spectrometry of mouse urinary metabolites.
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PLS-Based and Regularization-Based Methods for the Selection of Relevant Variables in Non-targeted Metabolomics DataMouse urinary biomarkers provide signatures of maturation, diet, stress level, and diurnal rhythm.Multivariate Analysis in Metabolomics.Systems level studies of mammalian metabolomes: the roles of mass spectrometry and nuclear magnetic resonance spectroscopy.The "secret" in secretions: methodological considerations in deciphering primate olfactory communication.Spectral multivariate calibration with wavelength selection using variants of Tikhonov regularization.Chemometric approaches to improve PLSDA model outcome for predicting human non-alcoholic fatty liver disease using UPLC-MS as a metabolic profiling tool
P2860
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P2860
Variable selection using iterative reformulation of training set models for discrimination of samples: application to gas chromatography/mass spectrometry of mouse urinary metabolites.
description
2009 nî lūn-bûn
@nan
2009年の論文
@ja
2009年論文
@yue
2009年論文
@zh-hant
2009年論文
@zh-hk
2009年論文
@zh-mo
2009年論文
@zh-tw
2009年论文
@wuu
2009年论文
@zh
2009年论文
@zh-cn
name
Variable selection using itera ...... of mouse urinary metabolites.
@en
Variable selection using itera ...... of mouse urinary metabolites.
@nl
type
label
Variable selection using itera ...... of mouse urinary metabolites.
@en
Variable selection using itera ...... of mouse urinary metabolites.
@nl
prefLabel
Variable selection using itera ...... of mouse urinary metabolites.
@en
Variable selection using itera ...... of mouse urinary metabolites.
@nl
P2093
P2860
P356
P1433
P1476
Variable selection using itera ...... of mouse urinary metabolites.
@en
P2093
Jose Trevejo
Kanet Wongravee
Maria Holmboe
Michele L Schaefer
Nina Heinrich
Randall R Reed
Richard G Brereton
P2860
P304
P356
10.1021/AC900251C
P407
P577
2009-07-01T00:00:00Z