ライフサイエンスコーパス: metabolomics

1 tes are additional challenges in single-cell metabolomics.

2 ction and quantification for high-throughput metabolomics.

3 were measured using targeted and untargeted metabolomics.

4 d lysis, cancer-related gene expression, and metabolomics.

5 of the common pipeline for data analysis in metabolomics.

6 e the onset of overt clinical symptoms using metabolomics.

7 MS is a viable and reproducible approach for metabolomics.

8 abled hyperpolarized natural abundance (13)C metabolomics.

9 g the first 6 mo postpartum using untargeted metabolomics.

10 available information on transcriptomics and metabolomics.

11 rimary cortical neurons using targeted polar metabolomics.

12 a applied for the first time to human faecal metabolomics.

13 esolution mass spectrometry-based untargeted metabolomics.

14 were investigated using ELISA and untargeted metabolomics.

15 tial least squares discriminant analysis for metabolomics.

16 copy (NIRS) and mass spectrometry (MS)-based metabolomics.

17 ation rates continue to be low in untargeted metabolomics.

18 complementing each other to perform salivary metabolomics.

19 of which require applying these theories to metabolomics.

20 ior to analysis with mass spectrometry-based metabolomics.

21 d compounds can be discovered in urine using metabolomics.

22 sequencing, and were deeply phenotyped using metabolomics, advanced imaging, and clinical laboratory

23 Untargeted metabolomics aims to quantify the complete set of metabo

24 The untargeted profiling based on UHPLC-QTOF metabolomics allowed annotating 316 compounds, comprisin

25 Combined proteomics and metabolomics analyses implicate an acquired metabolic ph

26 Transcriptomics, genome sequencing, and metabolomics analyses in these Zn-deficient rats reveale

27 the virus hijacking lipids for its benefit, metabolomics analyses indicated that DENV actively inhib

28 c consequences of both have been revealed by metabolomics analyses of circadian biology and sleep.

29 Metabolomics analyses of these RBC units were also perfo

30 viduals (n = 10) were quantified by targeted metabolomics analyses.

31 et metabolites using large-scale comparative metabolomics analysis across a database of 10,498 extrac

32 Based on data from microbial sequencing and metabolomics analysis demonstrating that young fecal tra

33 Metabolomics analysis of patient colon tumors (n = 197)

34 Further, metabolomics analysis revealed a S. parasanguinis-driven

35 Intracellular metabolomics analysis revealed decreasing levels of redo

36 Furthermore, metabolomics analysis suggested STP7 is a sugar starvati

37 Here, we used an untargeted metabolomics analysis to define system-level alterations

38 rm, offering better sensitivity for targeted metabolomics analysis.

39 ', unifying 'omics' (lipidomics, proteomics, metabolomics) analysis with native mass spectrometry to

40 Using high-resolution metabolomics and 16S rRNA gene sequencing, plasma/urine

41 preprocessing and postprocessing methods in metabolomics and also argues for a proper match between

42 Metabolomics and complex lipid profiling of cells and tu

43 yping of mutant parasites including targeted metabolomics and CRISPR-Cas9 fitness screening of all kn

44 e by including cutting-edge measures such as metabolomics and epigenetics.

45 ed with alterations in energy balance, blood metabolomics and fecal microbiota composition.

46 Here we effectively integrated metabolomics and gene expression data from breast cancer

47 Here, we combine metabolomics and genetics to characterize the cells' res

48 crobiomes of marine animals and cutting-edge metabolomics and genomic tools, we identified encouragin

49 We used metabolomics and in situ three-dimensional submicrometer

50 Plasma metabolomics and lipidomics (1871 biochemicals) revealed

51 Metabolomics and lipidomics are valuable tools for scree

52 Metabolomics and lipidomics studies are becoming increas

53 applied to shotgun and targeted analysis in metabolomics and lipidomics without requiring extensive

54 larger omics studies, including proteomics, metabolomics and lipidomics, as well as investigations o

55 For this purpose, untargeted metabolomics and molecular networking were used to obtai

56 Data processing strategies inspired from metabolomics and multi-targeted analysis were compared a

57 be used to build data-analysis workflows for metabolomics and other omics technologies.

58 esource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25 00

59 tional approach to recover missing values in metabolomics and proteomics datasets is important.

60 aim to give a timely overview of circulating metabolomics and proteomics findings with T2D observed i

61 Global metabolomics and proteomics profiling identified a FUNDC

62 Metabolomics and proteomics, facilitated by recent advan

63 Using a combination of untargeted metabolomics and RNA sequencing, we discovered a biosynt

64 The presented metabolomics and RNAseq data describe two distinct phyto

65 in a number of application areas, including metabolomics and small molecule identification, drug dis

66 Integrative analyses of metabolomics and transcriptomics (bulk and single-cell)

67 the approach with applications to untargeted metabolomics and transcriptomics data.

68 ly, serum and PBMCs samples were analyzed by metabolomics and transcriptomics, respectively.

69 advancement of 'omics' technologies, such as metabolomics, and (ii) an effort to redress the use of t

70 Combining genomics, transcriptomics, metabolomics, and biochemistry, we identify a CHS-L gene

71 erlapping associations with transcriptomics, metabolomics, and clinical endpoints suggest implication

72 r genomics, transcriptomics, proteomics, and metabolomics, and integrative analysis of these data, en

73 ditional research investigating epigenetics, metabolomics, and microbiome holds promise for novel bio

74 Integrated RNA sequencing, metabolomics, and molecular analyses showed that OXPHOS(

75 is study aims to model genetic, immunologic, metabolomics, and proteomic biomarkers for development o

76 rning model of transcriptomics, epigenomics, metabolomics, and proteomics.

77 le-body physiology, we performed lipidomics, metabolomics, and RNA-seq analyses on a mouse model.

78 ptional regulation, epigenetics, proteomics, metabolomics, and the microbiome.

79 By gathering genomics, metabolomics, and the sensory panel, we demonstrated tha

80 mode is more suitable for a given untargeted metabolomics application.

81 LC-MS based metabolomics approach revealed that putative metabolites

82 les were measured and an unbiased LCMS-based metabolomics approach was applied.

83 NMR metabolomics approach was used to distinguish fresh and

84 Using a metabolomics approach, the influence on primary and seco

85 omatography time-of-flight mass spectrometry metabolomics approach.

86 o results obtained from a classic untargeted metabolomics approach.

87 Then, two targeted metabolomics approaches, which employed triple quadrupol

88 rvations on chemical discovery in untargeted metabolomics are discussed.

89 We highlight the potential of metabolomics as a tool for understanding the molecular b

90 ation techniques remains underrepresented in metabolomics, as this analytical approach is still perce

91 Our study has limitations: our metabolomics assays measured only a small proportion of

92 We first performed targeted and quantitative metabolomics assays using capillary electrophoresis-mass

93 Metabolomics assessment identified markers of PTR and G6

94 graphy(u-PET), collagen quantification, lung metabolomics, assessment of antioxidant potential and so

95 Genomics and metabolomics associations identified 61 (5.1%) heterozyg

96 ing proteomics, transcriptomics, lipidomics, metabolomics, autoantibodies and immune cell profiling,

97 Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculat

98 handling is essential for the development of metabolomics-based blood tests, the results confirmed th

99 ates the potential of LC-SERS technology for metabolomics-based diagnosis and treatment of cancer.

100 atatas), and yam (Dioscorea spp.), following metabolomics-based diversity screening of global collect

101 platform for comprehensive and quantitative metabolomics-based exposome research with great utility

102 a and illustrate its merit by constructing a metabolomics-based score for biological age that capture

103 h factors may influence the accuracy of this metabolomics-based test in a clinical setting.

104 To date, (31)P NMR has seen limited usage in metabolomics because of a lack of reference spectra, dif

105 sms with AVNFH, transcriptomics, proteomics, metabolomics, biophysical, ultrastructural and histopath

106 We combine targeted metabolomics, biouptake and physiological response studi

107 gh-resolution LC-MS data for the purposes of metabolomics, but potentially it can be applied with sev

108 milar between men and women, suggesting that metabolomics can be a complementary approach to self-rep

109 the metabolism of PCB 11 and the associated metabolomics changes in HepG2 cells using untargeted hig

110 on a recently described combination of (13)C metabolomics combined with signal enhanced NMR via disso

111 and diversity of data being submitted by the metabolomics community.

112 A metabolomics comparison of Mtb-infected macrophages indi

113 Targeted metabolomics confirmed increased circulating levels of i

114 We previously demonstrated that serum metabolomics could distinguish RRMS from SPMS with high

115 method suitable for harmonizing large-scale metabolomics data and extending capabilities to quantify

116 In summary, we present a vast resource of metabolomics data and illustrate its merit by constructi

117 so argues for a proper match between type of metabolomics data and the biological question to be answ

118 coincident transcriptomics, proteomics, and metabolomics data at serial time points between admissio

119 for quantification supports harmonization of metabolomics data collected from 3677 human samples in 1

120 on of the complexity and redundancy of LC-MS metabolomics data comes from adduct formation.

121 enes in different tumors, and microarray and metabolomics data from Arabidopsis thaliana.

122 By integrating paired metagenomics and metabolomics data from existing cohorts with biochemical

123 However, whereas examination of metabolomics data from Oat-knockout mice (Oat1 and Oat3K

124 eir impact on metabolism using comprehensive metabolomics data from two population-based studies.

125 umptions that preclude direct integration of metabolomics data into the underlying models.

126 the fundamental structure and properties of metabolomics data is lagging behind.

127 e model approach to longitudinal analysis of metabolomics data provides an approach simultaneously fo

128 eveloped a novel algorithm, called Disparate Metabolomics Data Reassembler (DIMEDR), which attempts t

129 f untargeted high-resolution full-scan LC-MS metabolomics data remains challenging due to individual

130 Evaluation of metabolomics data reveals that AHRR methylation associat

131 n multiple omics data including genomics and metabolomics data to identify biomarkers potentially pre

132 We used endo- and exo-metabolomics data to show that the thermodynamic driving

133 istinguish at least four different levels of metabolomics data with different properties and warn aga

134 chromatography modification annotated yeast metabolomics data with similar effectiveness to growing

135 (clinical, transcriptomics, proteomics, and metabolomics data) and n = 312 for the validation cohort

136 312 for the validation cohort (clinical and metabolomics data).

137 ng DNA and RNA sequence data, proteomics and metabolomics data, to be captured from individuals and g

138 ls typically present in untargeted ESI-LC-MS metabolomics data.

139 large-scale targeted mass spectrometry-based metabolomics data.

140 roducing two fundamental theories concerning metabolomics data: data theory and measurement theory.

141 Three proteomics datasets and one metabolomics dataset indicate missing values could be a

142 first-pass alignment on a large-scale GCxGC metabolomics dataset.

143 he inconsistencies between incongruent LC-MS metabolomics datasets of the same biological sample type

144 Untargeted metabolomics depicted the phenolic composition of raw an

145 In critically ill children, NMR metabolomics differentiates well between those with a po

146 ization of (13)C isotope tracers and dynamic metabolomics documented that 5-PAHSA primes adipocytes f

147 Here we conducted a metabolomics-driven analysis followed by linear modellin

148 rger signal dispersion but is barely used in metabolomics due to ca. 6000-fold lower sensitivity.

149 , integrating the multivariate analysis with metabolomics enabled us to identify an elevation in the

150 Untargeted metabolomics experiments provide a snapshot of cellular

151 Here, through multiple (13)C-metabolomics experiments with Fe-replete and Fe-limited

152 ally increased the peak capacity for spatial metabolomics experiments.

153 ntial for health state diagnostics using all metabolomics features with data-driven analysis.

154 tially close buildings, revealing individual metabolomics features, retention time (rt) and mass-to-c

155 ive metabolic remodelling as demonstrated by metabolomics-fluxomics combined with bioinformatics and

156 tion (Bio-SPME) has shown great potential in metabolomics for in situ extraction of metabolites inclu

157 s; (ii) it is risk-disproportionate to apply metabolomics for regulatory purposes to search for possi

158 y (HRMS) combined with profiling qualitative metabolomics for the analysis of tryptophan degradation

159 contrast to transcriptomics, proteomics and metabolomics generate data that relate more directly to

160 Global untargeted metabolomics (GUM) has entered clinical diagnostics for

161 In the past decade, the field of LC-MS-based metabolomics has transformed from an obscure specialty i

162 technological advancements in sequencing and metabolomics have allowed for better characterization of

163 transcriptomics, epigenomics, proteomics and metabolomics, have all been applied to dissect the patho

164 es, including serology, transcriptomics, and metabolomics, have provided new insights into how we can

165 harmonization challenges for high-resolution metabolomics (HRM) data collected across different studi

166 Untargeted metabolomics identified 79 polar metabolites, 27 of whic

167 Recent advances in metabolomics illustrate that various metabolic pathways

168 lactolipids) and primary metabolism (through metabolomics) in two natural populations at different el

169 sion, changes in milk somatic cells and milk metabolomics indicated that heat stress affected the mam

170 Untargeted metabolomics indicates that the number of unidentified s

171 Thus, incorporating (31)P NMR into a metabolomics investigation will enable the detection of

172 Metabolomics is a powerful systems biology approach that

173 Metabolomics is emerging as an important field in life s

174 The major issue in untargeted metabolomics is linked to the lack of efficient ranking

175 Although untargeted metabolomics is often applied to understand the mode of

176 ective, relative to each of these areas: (i) metabolomics is unable to differentiate whether a mutati

177 ol samples, ncGTW applied to two large-scale metabolomics LC-MS datasets identifies many misaligned f

178 tory and co-expression networks, proteomics, metabolomics, lipidomics and phenomics with informatics

179 Integrating metabolomics, lipidomics, and transcriptomics, we link c

180 ng, microscopy, transcriptomics, proteomics, metabolomics, lipidomics, immunological assays, and flux

181 min and 14 days of recovery, analysed using metabolomics/lipidomics platforms and compared to exerci

182 Human milk metabolomics may be useful in predicting infant adiposit

183 cribed relating to COVID-19, indicating that metabolomics may open new avenues for understanding the

184 ecific metabolite reporters, and single-cell metabolomics may provide a means of exploring dynamic ac

185 We call this synthesis between ecology and metabolomics 'meta-metabolome ecology' and demonstrate i

186 l VOC profiling using a rapid-throughput VOC metabolomics method we refer to as 'simultaneous multifi

187 MS-based metabolomics methods are powerful techniques to map the

188 OmicsDI integrates proteomics, genomics, metabolomics, models and transcriptomics datasets.

189 Using untargeted metabolomics (n = 1,162 subjects), the plasma metabolite

190 logies reflective of edited affects, such as metabolomics, need to be used in a more prominent manner

191 The untargeted metabolomics not only confirmed the presence of amines,

192 feasibility of drug design based on knockout metabolomics of drug transporters.

193 Comparative metabolomics of plant tissues and excretions revealed th

194 Targeted metabolomics of plasma from an independent set of patien

195 Chromatography and untargeted metabolomics of the conditioned media, as well as transc

196 ng MS) is an enabling technology for spatial metabolomics of tissue sections with rapidly growing are

197 We used metabolomics on blood from artery, coronary sinus, and f

198 graphy-tandem mass spectroscopy (UPLC-MS/MS) metabolomics on maternal serum at 12, 20 and 28 weeks of

199 ics, metatranscriptomics, metaproteomics and metabolomics) on in situ samples over 14 months at weekl

200 To achieve this goal, metabolomics or 'non-targeted metabolite analysis' needs

201 eck for large-scale untargeted analyses like metabolomics or drug metabolite identification.

202 Metabolomics pathway enrichment analysis was performed o

203 have optimized and validated a multianalyte metabolomics platform for large-scale quantitative expos

204 Here we used a global metabolomics platform in a case-control study to compreh

205 A proton nuclear magnetic resonance metabolomics platform provided 230 metabolite measures:

206 throughput proton nuclear magnetic resonance metabolomics platform, which allows quantification of 14

207 ness of current mass spectrometry (MS) based metabolomics platforms is the time-consuming analysis an

208 Metabolomics plays a pivotal role in systems biology, an

209 The vaginal metabolomics profile of MIAC showed higher concentration

210 communities in their feces as well as serum metabolomics profile.

211 'Sweetheart': relatively susceptible) using metabolomics profiling and cell wall sugar characterizat

212 We used non-targeted metabolomics profiling to reveal metabolic pathways asso

213 9PT TNBC cells, along with LC-MS/MS and HPLC metabolomics profiling, we found here that exposure of T

214 Standardization of untargeted metabolomics protocols, including sample preparation, in

215 ems-scale analysis of cellular metabolites, "metabolomics," provides data ideal for applications in m

216 ingerprint and pathways of this disease make metabolomics-related approaches an indispensable tool fo

217 ists or biologists, researchers dealing with metabolomics require tools to decipher complex mixtures.

218 With the growth of metabolomics research, more and more studies are conduct

219 In the field of metabolomics research, this issue has largely remained u

220 try metabolite profiling is the workhorse of metabolomics research.

221 Cholecystectomy impacted the global metabolomics responses to RYGB, and patients who underwe

222 s, many unidentifiable signals in untargeted metabolomics result from the latter rather than new comp

223 gnitive computing-assisted analysis of these metabolomics results helped to prioritize potential acti

224 Complementing our metabolomics results, our transcriptomics analyses also

225 In our study in mice, metabolomics revealed increased fecal concentrations of

226 Milk metabolomics revealed that citrate increased by HS, wher

227 NMR-based metabolomics revealed that inulin-enrichment increased t

228 Non-targeted metabolomics revealed that UV-B has a strong impact on p

229 rcial kratom products using untargeted LC-MS metabolomics, revealing two distinct chemotypes that con

230 es for integrative longitudinal analysis for metabolomics scientists and various visualization functi

231 tepwise regression analysis contributed to a metabolomics score as a predictor of diet quality.

232 : see text] nuclear magnetic resonance (NMR) metabolomics, Seahorse, and the spatial distribution of

233 ne gas analysis and high-resolution temporal metabolomics showed oscillations in gas uptake rates and

234 Here, we first show that metabolomics software packages developed for automated o

235 Metabolomics stands out here as one of the most powerful

236 e, we present a mass spectrometry (MS)-based metabolomics strategy that only consumes sub-nanoliter s

237 omatography (HILIC) is gaining popularity in metabolomics studies due to its enhanced performance ove

238 nostic yield of both targeted and untargeted metabolomics studies is low when assessing patients with

239 Our metabolomics studies revealed that cis-polyisoprenoids a

240 e human studies as well as key findings from metabolomics studies using mice, Drosophila, and zebrafi

241 dels for health state-prediction in 35 human metabolomics studies, representing 148 individual data s

242 MetaboLights is a database for metabolomics studies, their raw experimental data and as

243 BSCAN and OPTICS) that were used in previous metabolomics studies.

244 l approach in spatially-resolved single cell metabolomics studies.

245 s in one of the largest non-targeted urinary metabolomics study to date demonstrate the role of the u

246 alable data processing capacity for targeted metabolomics, substantially curtailing the time required

247 was determined using mass spectrometry-based metabolomics targeting nutrients and bioactive metabolit

248 Among metabolomics techniques, NMR spectroscopy is a sophistic

249 However, leading metabolomics technologies, such as NMR and mass spectrom

250 o further validate the high accuracy of this metabolomics test and to determine if this is maintained

251 We demonstrate by unbiased and targeted metabolomics that the mammalian brain oxidizes a substan

252 nstruction and functional studies coupled to metabolomics that unravel the interplay between biosynth

253 We also measured child serum metabolomics through a targeted assay and found signific

254 -quality quantitative analysis in untargeted metabolomics, thus providing more confident biological h

255 cal utility of GUM with traditional targeted metabolomics (TM) as a screening tool in patients with e

256 l culture media, and mass spectrometry-based metabolomics to detect and quantify (13)C-labeled metabo

257 We aimed to use non-targeted urine metabolomics to discover biomarkers and improve risk pre

258 ased in many application fields ranging from metabolomics to environmental science.

259 e, we introduce a workflow for dose-response metabolomics to evaluate chemicals that potentially affe

260 Here, we used RNA-sequencing and metabolomics to examine early glaucoma in DBA/2J mice.

261 we primarily focus on applying dose-response metabolomics to find off-target effects of drugs.

262 It has been argued that the application of metabolomics to gene-edited crops would present value in

263 table isotopes are routinely employed by NMR metabolomics to highlight specific metabolic processes a

264 work, we propose a method based on targeted metabolomics to identify the polyphenols present in seed

265 iplinary approach including isotope-resolved metabolomics to show that in Drosophila melanogaster, Ac

266 y, we combined photobiology, proteomics, and metabolomics to understand the underlying role of sustai

267 However, spatial metabolomics tools often lack the sensitivity, specify,

268 sponses beyond those that can be measured by metabolomics, TOXcms also accepts data from respirometry

269 rough real-time bioenergetic measurement and metabolomics upregulated glycolysis and suppressed oxida

270 of fatty acid synthesis enzymes and targeted metabolomics using a mouse model and human specimens.

271 Metabolomics using nontargeted tandem mass spectrometry

272 Untargeted metabolomics was conducted using a Q-Exactive Hybrid Qua

273 Global, untargeted metabolomics was conducted via ultra performance liquid

274 Mass spectrometry-based metabolomics was performed on 24-hour urine samples coll

275 Untargeted metabolomics was performed on plasma from ALS participan

276 An untargeted UPLC/MS-based metabolomics was performed to discover metabolites profi

277 Metabolomics was performed using a high-throughput proto

278 eted liquid chromatography-mass spectrometry metabolomics was used to determine longitudinal metaboli

279 In the first step, untargeted metabolomics was used, which employed high-resolution, a

280 Following treatment, targeted metabolomics was utilized to evaluate myocardial substra

281 autochthonous STS murine models and unbiased metabolomics, we demonstrate that glutamine metabolism s

282 a-high-performance LC-MS/MS- and GC/MS-based metabolomics, we found that, as a global transcriptional

283 By combining this genetic tool with metabolomics, we identify circulating alpha-hydroxybutyr

284 o facilitate the application of (31)P NMR in metabolomics, we present a unified protocol that allows

285 graphy-mass spectrometry-based (LC-MS-based) metabolomics, we profiled more than 1600 molecules in re

286 Using comparative metabolomics, we show that a pathway mediating formation

287 Stable-labelled isotopes and metabolomics were employed to address the influence of n

288 Milk metabolomics were evaluated using (1)H nuclear magnetic

289 hotgun metagenomic sequencing and untargeted metabolomics were performed on stool samples.

290 tegy has the potential to fill in the gap in metabolomics where liquid chromatography-MS-based analys

291 genomic/epigenetic markers, microbiome, and metabolomics will be measured in older adult women sampl

292 Recent advances integrating metabolomics with genomics are discussed, yielding new i

293 n plant phytochemistry, we combined targeted metabolomics with insect herbivore bioassays and with a

294 d sensory quality, by integrating non-target metabolomics with sensory data.

295 Integration of metabolomics with the on-going genomic and phenotypic st

296 However, some adjustments of the metabolomics workflow are needed before HRMS-based metho

297 Herein, we describe an improved GC-MS-based metabolomics workflow that uses insoluble protein-derive

298 Moreover, glycogen is measured within the metabolomics workflow.

299 We then employ metabolomics workflows utilizing gas chromatography mass

300 We hypothesized stable isotope metabolomics would identify increased glucose, glutamine