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1  gene expression, genotyping, proteomics and metabonomics.
2 h particular application in metabolomics and metabonomics.
3 ion of international reporting standards for metabonomics.
4 ne of the central approaches in the field of metabonomics.
5 bility PCR, 16S rRNA sequencing and 1(H) NMR metabonomics.
6 y of similar but not identical proteomic and metabonomic alterations in the chronic PCP rat model and
7 study presents temporal comparative (1)H NMR metabonomic analyses of filamentous phage pf1 infection
8                                Proteomic and metabonomic analyses showed that the MAM treatment on E1
9                                            A metabonomic analysis allowed us to highlight the evoluti
10  for high-throughput targeted UPLC-ESI-MS/MS metabonomic analysis in clinical and epidemiological env
11  the NMR spectrum of honey and its classical metabonomic analysis is completely dominated by a very f
12 authors recently proposed an approach to the metabonomic analysis of biofluid mixtures based on the u
13 ethod that is well suited to high-throughput metabonomic analysis of complex mixtures such as urine c
14                                              Metabonomic analysis of urine from these animals reveale
15                                              Metabonomic analysis showed differences between sham con
16                                              Metabonomic analysis using 1H Magic Angle Spinning Nucle
17  NMR peaks is required to enable comparative metabonomic analysis using 2D NMR.
18 ed to analyse changes in the microbiome, and metabonomic analysis was performed using proton nuclear
19 entified by nuclear magnetic resonance-based metabonomic analysis.
20 as some significant advantages over standard metabonomic analysis.
21 mbined with statistical analysis for further metabonomics analysis and biomarker identification.
22                                              Metabonomic analytical approaches have now been translat
23 ial will also provide opportunity to conduct metabonomic and gut microbiome studies as explorative an
24 ogical and biochemical means supplemented by metabonomic and microarray techniques.
25            591 patients participating in The Metabonomics and Genomics in Coronary Artery Disease (Ma
26                    Such collections arise in metabonomics and many other applications.
27  including metabolic profiling (metabolomics/metabonomics) and lipidomics, are making a significant i
28                                       Here a metabonomic approach based on chemometric analysis of 1H
29               This study describes the first metabonomic approach to determining biochemical modifica
30 es in biofluid composition than the standard metabonomic approach using complete 1D proton NMR spectr
31                                   By using a metabonomics approach (termed "NObonomics") for detailin
32 rofiles can be selectively amplified using a metabonomics approach based on the different NMR spectra
33 oney samples, a comparison of this classical metabonomics approach to one based on the use of the sel
34 n alternative and conceptually new 'pharmaco-metabonomic' approach to personalizing drug treatment, w
35 mbined immunofluorescent, transcriptomic and metabonomic approaches.
36 olic subcompartments as well as conventional metabonomics concentration-based diagnostics.
37  applied to nuclear magnetic resonance (NMR) metabonomic data sets.
38 rmation on the physicochemical variations in metabonomic data sets.
39 ers a new powerful framework for analysis of metabonomic data.
40 arized CCA and correlation analyses of urine metabonomics data and 16S rRNA gene sequencing data to i
41 ciations between specific longitudinal urine metabonomics data and microbiome data in a diet-induced
42                                   Integrated metabonomics data assessment methodology should facilita
43 PLS allowed us to explore longitudinal urine metabonomics data in relation to the dietary groups, as
44 riptome and nuclear magnetic resonance-based metabonomics data.
45 ection and influence statistical analysis of metabonomics data.
46 ne-expression profiling, metaproteomics, and metabonomics, differences in microbial composition and f
47 y should facilitate translation of NMR-based metabonomics discovery of human disease biomarkers to cl
48 better approximate background variation in a metabonomics experiment is presented.
49                   Based on the proteomic and metabonomic findings, we were able to develop a schemati
50 tegy combining pharmacokinetics, toxicology, metabonomics, genomics, and metagenomics to elucidate an
51                                              Metabonomics is an advancing field in systems biology, w
52                             Modern NMR-based metabonomics is elucidating contaminant toxicity and tox
53           Metabolite profiling (metabolomics/metabonomics) is a powerful means of assigning phenotype
54 identification, impurity identification, and metabonomic/metabolomic studies.
55 nd cotton ball brands be characterized using metabonomics methodologies prior to initiating a metabon
56 nimals and show that it is possible to apply metabonomics methodology to this important class of biof
57 sis of metabolic data and shows the value of metabonomic methods in the investigation of physiologica
58                                              Metabonomic methods utilizing (1)H NMR spectroscopy and
59 ma profiles generated by a key technology in metabonomics, NMR spectroscopy.
60 presents diagnostic potential for studies by metabonomics of mass-limited biopsies.
61                                              Metabonomics offers a posttranscriptional view of system
62  spectra is an important tool in large-scale metabonomic or metabolomic studies, where hundreds or ev
63 vatives, their impact on the composition and metabonomic profile of a defined community of human gut
64                                          The metabonomic profile was also affected by free and immobi
65 val plaque microbiota structure and salivary metabonomic profiles.
66 used functional genomic approaches including metabonomic profiling and gene expression analyses to id
67 aphy-mass spectrometry (LC-MS) proteomic and metabonomic profiling approaches on prefrontal cortex (P
68  and proton nuclear magnetic resonance-based metabonomic profiling of the rat frontal cortex after ch
69                                              Metabonomic profiling revealed changes in the levels of
70                                              Metabonomic profiling substantiated the proteomic findin
71                                              Metabonomic profiling techniques, with established quali
72 ating existing postgenomic data with current metabonomic results in P. aeruginosa biofilms research.
73 romatography/mass spectrometry (LC/MS) based metabonomics screening of urine has great potential for
74 onal genomic, transcriptional, proteomic and metabonomic signatures to characterize drug mechanisms a
75                                 We applied a metabonomic strategy to identify host biomarkers in seru
76 fication of potential biomarker molecules in metabonomic studies based on NMR spectroscopic data.
77                                              Metabonomic studies implicated variations in gut microbi
78         Metabolic profiling, metabolomic and metabonomic studies mainly involve the multicomponent an
79         Metabolic profiling, metabolomic and metabonomic studies require robust study protocols for a
80                                              Metabonomic studies should encompass a representative "f
81 omplicates biomarker information recovery in metabonomic studies when using multivariate statistical
82 s large sample cohorts common in metabolomic/metabonomic studies, we have developed a prealignment pr
83 rs, ensuring its suitability for large scale metabonomic studies.
84 ng by 2D NMR as a routine method for various metabonomic studies.
85 across the multiple (1)H NMR spectra used in metabonomic studies.
86 ncreasing the fingerprint coverage for LC-MS metabonomic studies.
87  (MS) is increasingly being used for urinary metabonomic studies.
88 nfluence the outcome of NMR- and LC/MS-based metabonomics studies of human infant urine.
89 d potentially influence NMR- and LC/MS-based metabonomics studies.
90 o identify biomarkers both in proteomics and metabonomics studies.
91 s, which are sometimes vitally important for metabonomics studies.
92 en applied to 1H NMR spectra of urine from a metabonomic study of a model of insulin resistance based
93                         We conducted a serum metabonomic study to explore the potential biomarkers of
94       A nested population-based case-control metabonomic study was first performed on 40 DR cases and
95 a set of metabolites (e.g. biomarkers from a metabonomic study) and plots the connectivity between me
96 bonomics methodologies prior to initiating a metabonomics study to ensure that contaminant profiles a
97 ng an artificial data set and spectra from a metabonomics study.
98                                              Metabonomics techniques of data reduction and pattern re
99 se of nuclear magnetic resonance (NMR)-based metabonomics to search for human disease biomarkers is b
100                           The Consortium for Metabonomic Toxicology (COMET) obtained temporal NMR spe
101 er project lead by the COMET (Consortium for Metabonomic Toxicology).
102                  In general, applications of metabonomics using biofluid NMR spectroscopic analysis f
103 ectra or mixtures of compounds, as in chiral metabonomics, where severe overlapping exists in proton

 
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