ライフサイエンスコーパス: covariance

1 % CI, 0.56-1.37 hours; P < .001, analysis of covariance).

2 the stochastic variables (mean, variance and covariance).

3 718 and placebo groups (P = .04, analysis of covariance).

4 able through reducing mortality and altering covariance.

5 onparametric randomization-based analysis of covariance.

6 ated by drought-tolerant species showed weak covariance.

7 argely due to increased cortical-subcortical covariance.

8 el such as linear regression and analysis of covariance.

9 nge, stable isotope discrimination, and eddy covariance.

10 toparietal cortices, as shown by analysis of covariance.

11 pairs with statistically significant genetic covariance.

12 wo notions of the effective rank of the data covariance.

13 development were tested by using analysis of covariance.

14 pecies-specific intercepts using Analysis of Covariance.

15 of evergreen conifer stands measured by eddy covariance.

16 toparietal cortices, as shown by analysis of covariance.

17 IVH) over 24 h were estimated in analyses of covariance.

18 Results were analyzed using analysis of covariance.

19 nto quartiles based on the strength of their covariance.

20 In analysis of covariance, 1p/19q co-deletion status was the only signi

21 eQTLs and the major axes of gene expression covariance, a highly significant excess of variants with

22 t disentangling common and unique sources of covariance across genetically similar phenotypes as the

23 Analysis of covariance, adjusted by baseline PI, was the main analys

24 We performed analysis of covariance, adjusted for model for end-stage liver disea

25 E categories were compared using analysis of covariance adjusting for age, sex and education.

26 Analyses of covariance, adjusting for age and sex, examined differen

27 In some analyses for years 1-3, analysis of covariance adjustment indicated that this DSAEK-associat

28 Through the use of analysis of covariance, all (18)F-FDG PET brain images of MMF patien

29 al markets, we measured temporally conserved covariance among bacterial taxa in the microbiota of hea

30 among stressors and the genetic variance and covariance among fitness-related traits that may reinfor

31 a baseline 1958-1987 period that account for covariance among four variables important to Earth's bio

32 Theory indicates that if covariance among functional traits sets a limit on the n

33 al framework in order to examine patterns of covariance among herbivorous and predatory arthropod gui

34 ounts for both additive and dominant genetic covariance among individuals, and decomposes single-nucl

35 hods for longitudinal GWAS either ignore the covariance among observations of different time points o

36 mon consequence, not the common cause of the covariance among tests is more in line with an evolution

37 linked selection over short timescales using covariance among time points and across replicates.

38 Positive covariance amongst vital rates and temporal variation in

39 Evolutionary covariance analysis allowed tracing of the a subunit seq

40 Interregional covariance analysis revealed that these intracortical ch

41 tical regions was quantified with structural covariance analysis.

42 Analysis of covariance (ANCOVA) adjusted for age and Cox regression

43 Using analysis of covariance (ANCOVA) after last observation carried forwa

44 Analysis of covariance (ANCOVA) analysis revealed that differences b

45 A One-way Analysis of Covariance (ANCOVA) was conducted to evaluate the mean d

46 nalysis (p = 1.56 x 10(-4) in an analysis of covariance (ANCOVA) with an adjustment for unknown laten

47 The recommended solution is an analysis of covariance (ANCOVA), but it is rarely used, possibly bec

48 the typical flight path, (2) the modeling of covariance and anisotropy, and (3) the type of interpola

49 iven sequence samples via a battery of cross-covariance and auto-covariance transformations.

50 process model MAESTRA, and (2) combined eddy covariance and chamber respiration data.

51 hen used as seeds for exploratory anatomical covariance and connectivity analyses.

52 Covariance and correlation based PCA are two common appr

53 Analysis of covariance and exact Mann-Whitney tests were used to com

54 leotide composition, dinucleotide-based auto covariance and global information of the entire samples

55 selection by regularization governed by the covariance and inverse covariance matrices of explanator

56 Analysis of covariance and multivariate linear regressions were cond

57 Analysis of covariance and paired-sample t tests were used for stati

58 optimum, using measurements of in situ eddy covariance and satellite-derived proxies, and report its

59 Analysis of covariance and Spearman rank correlation test for cross-

60 es responses were compared using analysis of covariance and trait-gradient analysis.

61 hods, our method is able to find significant covariances and also to control false discovery rates, e

62 atistical (one-way between-group analyses of covariance) and clinical effects (clinically significant

63 ality), vital rate stochasticity, vital rate covariance, and periodic catastrophes.

64 y responses will depend on genetic variance, covariance, and their interaction across development and

65 rare variants using a nonparametric distance-covariance approach that compares similarity in multivar

66 ain regions and brain networks of structural covariance, as measured by ex vivo structural magnetic r

67 ded the most powerful single trait set test, covariance association test (CVAT), to a multiple trait

68 Here, we apply covariance-based detection to nonlinear optical spectros

69 Covariance-based discovery of polymorphisms under co-sel

70 hese proof-of-principle results suggest that covariance-based nonlinear spectroscopy will improve the

71 In contrast, covariance-based techniques used in photoionization elec

72 promising signal comes from the genome-wide covariance between allele frequency changes observable f

73 eritability of height is due to the positive covariance between allelic effects at different loci, wh

74 s were the major contributor to the negative covariance between BW and future cardiometabolic risk.

75 This view is supported by inverse covariance between delta(13)C and a range of uplift prox

76 (ii) Has the genetic covariance between fitness (as measured by total fertili

77 ed by drought-avoiding species showed strong covariance between greenness and SPEI, while those domin

78 tion, and exemplify how it can reveal shared covariance between histone modifications and DNA binding

79 In particular, we found strong genetic covariance between late-onset Alzheimer disease (LOAD) a

80 le mating success (Bateman gradient) and the covariance between male mating success and postcopulator

81 By contrast, the covariance between maximum height and seed mass strength

82 etic factors contribute significantly to the covariance between myopia and intelligence.

83 gression models identified sources of signal covariance between neuroinflammation and brain connectiv

84 r, common garden studies have demonstrated a covariance between neutral markers and functional traits

85 This study shows compelling evidence for covariance between personality and pace-of-life in a nat

86 We conclude that the covariance between random effects is a key parameter for

87 ed CORE GREML, that explicitly estimates the covariance between random effects.

88 ps showed significantly increased structural covariance between regions with cortical thickness reduc

89 ency of these groups across Europe, and some covariance between shell colour and banding patterns.

90 cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were obser

91 ive maternal and a negative additive genetic covariance between these two.

92 rk to estimate annotation-stratified genetic covariance between traits using GWAS summary statistics.

93 so quantify the among-individual and genetic covariances between personality and size and growth, whi

94 Our results, which are among the first eddy covariance CH(4) exchange data reported for any tropical

95 ing spring thaw and autumn freeze using eddy covariance CH(4) measurements from three Arctic sites wi

96 Eddy covariance CO(2) flux measurements showed that air tempe

97 in a co-regulated DGP have higher expression covariance compared with the separate, tandem and conver

98 e also identify signals of negative temporal covariance corresponding to reversals in the direction o

99 Here we use empirical models based on eddy covariance data and process-based models to investigate

100 database consists of 143 site-years of eddy covariance data from 22 inland wetland and 21 coastal we

101 re we address this observation gap with eddy covariance data from 25 sites in the water-limited South

102 carbon flux model, MAESTRA, to predict eddy covariance data from a loblolly pine forest.

103 el to 7 years (2008-2014) of continuous eddy covariance data from a snow-scoured alpine tundra meadow

104 As a result, we leveraged eddy covariance data from six evergreen conifer forest sites

105 mates for the same site and years using eddy covariance data only.

106 0% of the average seasonal variation in eddy covariance-derived CO2 assimilation.

107 ition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen for

108 .76%; P = 0.223 and P = 0.403 by analysis of covariance) did not reach significance.

109 a single trait pair for which the cross-sex covariances differed (i.e., COV(A(m,f)) != COV(A(f,m))).

110 stinct influences on fMRI signals and signal covariance, distinct timescales, distinct cardiovascular

111 Eddy covariance (EC) continues to provide invaluable insights

112 mating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally.

113 l coniferous forests was explored using eddy-covariance (EC) energy and CO2 fluxes.

114 isotope analysis, leaf gas exchange and eddy covariance (EC) fluxes.

115 on rice field CH(4) emissions using the eddy covariance (EC) method.

116 Flux measurements based on the eddy covariance (EC) technique can overcome these limitations

117 The eddy covariance (EC) technique is used to measure the net eco

118 velop an empirical Bayes approach to improve covariance estimates for gene expression, where we assum

119 e conventional GREML, providing variance and covariance estimates free from bias due to correlated ra

120 emonstrate that our method provides accurate covariance estimates, thereby enabling researchers to di

121 ct coupling analysis (mfDCA), sparse inverse covariance estimation (PSICOV), classical neural network

122 eepCov, which was trained on 441 matrices of covariance features.

123 Here we report simultaneous eddy covariance flux measurements of NOx, CO2, CO and non met

124 tland sediment methane, ecosystem-scale eddy covariance flux observations, and laboratory incubation

125 n plant physiology, remote sensing, and eddy covariance flux observations.

126 d successfully predicts GPP measured at eddy-covariance flux sites.

127 In this study, we combine nested eddy covariance flux tower measurements with satellite remote

128 Using nested eddy covariance flux towers, we find both GPP and ER to be la

129 to altered nutrient stoichiometry using eddy covariance fluxes measurements, satellite observations,

130 total coordination (sum of all the pairwise covariances) following training than a technique-trained

131 resent a lower bound to the estimation error covariance for a noisy initial probe state evolving thro

132 variances, genetic correlations, and genetic covariances for 18 domestication-related traits using re

133 ndom effects, where the mean surface and the covariance function is specified.

134 Structural covariance global metrics suggested a potential differen

135 behavioural profiles and, hence, lower trait covariance in a population.

136 can control for and estimate spatial-social covariance in disease ecology analyses.

137 variable explained 31% of the brain-clinical covariance in iRBD, combining cortical and subcortical d

138 effects explain a greater proportion of the covariance in males, whereas the association is primaril

139 Rate covariance in PC inputs also accounts for the high coeff

140 how clusters can decompose the variance and covariance in risk for disease, thereby identifying unde

141 resent a lower bound to the estimation error covariance in the most general form for a noisy initial

142 igned with the additive genetic variance and covariance in traits.

143 r the quantification of [(18)F]FDG brain PET covariance, including the definition of an entropy metri

144 We found positive and negative covariances indicative of epidemiological interactions a

145 ss, indicating that climate effects on trait covariance indirectly influence diversity at local scale

146 on and mode of dinucleotide-based auto-cross covariance into an ensemble classifier of clustering app

147 ing was used to decompose the cross-disorder covariance into genetic and environmental factors.

148 lizes a decomposition of trait variances and covariances into genetic and environmental parts.

149 d convergent configurations, and this higher covariance is caused by more synchronized firing of the

150 ar boreal forest-wetland landscapes and eddy covariance landscape net CO2 flux measurements suggest a

151 ss-sectional level, multivariate analysis of covariance (MANCOVA) was conducted to examine potential

152 tient sample, using multivariate analyses of covariance (MANCOVA) we compared cognitive performance o

153 teosinte and maize landrace genetic variance-covariance matrices (G-matrices).

154 iatric phantom testing yielded similar noise covariance matrices and only slightly degraded SNR for t

155 a spiked model similar to that employed for covariance matrices as a framework to study PCA.

156 Covariance matrices between kinematic measures were comp

157 were computed and distances between pairs of covariance matrices calculated using Riemannian geometry

158 ation governed by the covariance and inverse covariance matrices of explanatory variables.

159 for brain PET studies using population-based covariance matrices, with the aim to explore topological

160 residue-level protein contacts using inverse covariance matrix (or precision matrix) of multiple sequ

161 Both this map and the learned covariance matrix can be used as a structured prior for

162 ation based on 4 elements of a 9 x 9-element covariance matrix for nine cluster properties, measured

163 ssociated with the largest eigenvalue of the covariance matrix is helpful for identifying the regions

164 dy, we propose the use of eigenvalues of the covariance matrix of multiple time series as early warni

165 model transformation was used to whiten the covariance matrix of polygenic matrix K and environmenta

166 hm of model transformation that whitened the covariance matrix of the polygenic matrix K and environm

167 rs lies in the small-eigenvalue modes of the covariance matrix of the selected sequences.

168 cious block decomposition of the conditional covariance matrix such that the evolutions of different

169 tes for gene expression, where we assume the covariance matrix takes a block diagonal form.

170 oad impact eQTL when constructing the sample covariance matrix used for the random effect in a mixed

171 y assumption or regularity conditions on the covariance matrix, but directly analyzes the composition

172 ntact-maps compared with the previously used covariance matrix.

173 ncertainty around this mean in the form of a covariance matrix.

174 with a random intercept and an unstructured covariance matrix.Short-term changes in energy intake (P

175 Eddy-covariance measurements are widely used as the closest '

176 e we evaluated 121 site-years of annual eddy covariance measurements of net and gross CO2 exchange (p

177 We combined these data with concurrent eddy-covariance measurements of whole-ecosystem CO2 and CH4 e

178 oprene emission estimates from aircraft eddy covariance measurements over the Amazonian forest.

179 the mean flow and fluxes from aircraft eddy-covariance measurements over the tropical Eastern Pacifi

180 4) in a mangrove wetland with long-term eddy covariance measurements.

181 ne mangrove wetland based on 3 years of eddy covariance measurements.

182 nts, and for the whole forest using the eddy covariance method.

183 a, USA, from 2001 through 2019 with the eddy covariance method; during this 19-year period, CO(2) ros

184 ametric Kruskal-Wallis tests and analysis of covariance methods were used to evaluate the diagnostic

185 etween treatment groups using an analysis of covariance model that adjusted for baseline distance con

186 lculated using repeated measures analysis of covariance model that adjusted for treatment and baselin

187 cleotide alignment of the full sequence to a covariance model.

188 able Cox regression model and an analysis of covariance model.

189 Multivariate analysis of covariance models (ANCOVA) was constructed in a stepwise

190 ecmarker, a method based on manually curated covariance models capturing the specific tRNASec structu

191 Using nested wetland and landscape eddy covariance net CH4 flux measurements in combination with

192 m respiration across the global FLUXNET eddy-covariance network and identify a pervasive influence th

193 nificantly thinner cortex in five structural covariance networks (insular-limbic, occipito-temporal,

194 calculated intra-individual brain structural covariance networks (using the bilaterally-averaged valu

195 compare topological properties of structural covariance networks and hub regions.

196 Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OC

197 a less segregated organization of structural covariance networks in OCD, and reorganization of brain

198 controls, at a global level, the structural covariance networks of OCD showed lower clustering (P <

199 Structural covariance networks predicted psychopathology symptoms a

200 Brain structural covariance networks reflect covariation in morphology of

201 s and visualization tool that we use to find covariance networks that can predict molecular functions

202 of follow-up data revealed that 11 of the 24 covariance networks were associated with irritability, w

203 Structural covariance networks were delineated using non-negative m

204 Structural covariance networks were derived using nonnegative matri

205 cortical thickness data to derive structural covariance networks.

206 d sensitivity for NMR spectra than classical covariance NMR reducing offset-dependent artifacts.

207 spectra combining Fourier transformation and covariance NMR.

208 Here, we use eddy covariance observations from globally distributed and au

209 This covariance of [ATP] with [5-InsP7] provides direct suppo

210 We identified a strongly positive covariance of both cation (Ca(2+), Mg(2+), K(+), Na(+))

211 differences in the rate, sequence, phase, or covariance of firing.

212 ying genetic architecture of gene regulation.Covariance of gene expression pairs is due to a combinat

213 t a marked global increase in inter-regional covariance of MOR availability in schizophrenia, largely

214 nal canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as c

215 al filter, whose weights were adapted to the covariance of ongoing LFP.

216 ays and knowledge bases, and analysis of the covariance of ovary gene expression with surface water c

217 Analyses of the correlation or covariance of regional brain structure and function appl

218 Furthermore, the trial-by-trial covariance of the induced responses recapitulated the pa

219 epeated effect of time was used to model the covariance of the residuals with an unstructured matrix.

220 ty, and technical noise to the variances and covariances of absolute bacterial abundances.

221 geneity of gut microbiota, and high temporal covariances of taxa within the Bacteroidetes phylum.

222 We employed a three-way analysis of covariance on FC to conduct statistical analyses.

223 near Poisson modelling advances pLSA, giving covariances on model parameters and supporting chi2 test

224 Here, we examine how temporal covariance (or differentiation) in voxel representations

225 mean 25+/-5 versus 31+/-6 mm Hg; analysis of covariance P=0.022).

226 conds for conventional settings (analysis of covariance; P=0.044 between groups) despite lower peak m

227 ble individual salience dimensions and their covariance pattern replicated across samples from three

228 component analysis (PCA) identifying spatial covariance patterns.

229 From GW association and analysis of covariance performed on a total sample of 429 Peruvian Q

230 d reveals sustained systematic stratigraphic covariance, precluding nonatmospheric explanations.

231 By studying examples of data covariance properties that this characterization shows a

232 Patterns of structural covariance (PSCs) derived by NMF were highly reproducibl

233 coordinates (dpPCA) as options to construct covariance (Q) or correlation (R) matrices.

234 intercept per individual and an unstructured covariance R matrix was used as correlation structure.

235 These temporal covariances reflect how heritable fitness variation in t

236 oric theory enables a data-driven mapping of covariance relationships in single-cell measurements int

237 Multivariate analyses of covariance revealed a significant multivariate main effe

238 A nested mixed model analysis of covariance revealed that the intervention was successful

239 lation-based matrices describing the spatial covariance (SCV) relationships that link genetic diversi

240 ne/co-chaperone system to adjust the spatial covariance (SCV) tolerance and set-points on an amino ac

241 An analysis of covariance showed that lower BIS scorers exhibited large

242 Analysis of covariance showed that mean IOP reduction with LBN was n

243 des and represents acoustic regularities and covariance.SIGNIFICANCE STATEMENT The efficient coding (

244 Here we show, using data from 42 eddy covariance sites across six major biomes, that ecologica

245 s during periods of water stress at two eddy covariance sites in Australia.

246 piration and biomass, to create virtual eddy covariance sites in the sky.

247 This study shows that covariance statistics can be applied to PET neuroimaging

248 ymmetry of the cross-trait cross-sex genetic covariance structure (submatrix B).

249 intercept for reader, and compound symmetry covariance structure for lesion.

250 vity patterns, we can directly estimate this covariance structure from imaging data.

251 entational similarity, in which we treat the covariance structure of neural activity patterns as a hy

252 The covariance structure of personality traits derived from

253 hidden units to most effectively capture the covariance structure of the input data.

254 d analytically using the asymptotic variance-covariance structure of the parameter estimator, or else

255 is tests about the mean relationship and the covariance structure within the rows and columns.

256 imate choice because it accounts for complex covariance structure; however, high computational costs

257 Our study identifies the set of covariance structures for the upstream cells that optimi

258 selection-based procedures to tackle complex covariance structures of gene-gene interactions.

259 Thus, covariance structures that maximize information in neura

260 mework for the Gaussian model with arbitrary covariance structures.

261 of this study, the largest brain structural covariance study of OCD to date, point to a less segrega

262 these rates often exhibit positive temporal covariance, suggesting that vital rates respond to commo

263 orrelations between traits revealed positive covariances, suggesting that selection to multiple stres

264 uate to explain the observations of the eddy-covariance systems, which must now be questioned for the

265 Analysis of covariance, taking the baseline IOP as a covariate, reve

266 e flux (FCH(4) ) measurements using the eddy covariance technique have increased over the past decade

267 p forest in Sarawak, Malaysia using the eddy covariance technique over 4 years from 2011 to 2014.

268 ave reported anomalous CO2 uptake using eddy-covariance techniques in arid and semiarid ecosystems.

269 -effects repeated measures model analysis of covariance that included data from all available stages

270 eory predicts a set of symmetries of barcode covariance that serves as a consistency check for the va

271 The authors used multivariable analysis of covariance to compare high-density lipoprotein particle

272 ead to temporal covariance, we can use these covariances to estimate what fraction of the variation i

273 pulations by adding features' dispersion and covariances to population averages, in the context of im

274 (BAnOCC: Bayesian Analysis of Compositional Covariance) to estimate a sparse precision matrix throug

275 riment, a forest chronosequence, and an eddy-covariance tower for model parameterization and evaluati

276 this goal, we used data from six paired eddy-covariance towers over co-located forests and grasslands

277 exchanges at the landscape scale using eddy covariance towers over two land-cover types in tropical

278 from a network of temperate and boreal eddy covariance towers, satellite data, plant trait datasets,

279 s via a battery of cross-covariance and auto-covariance transformations.

280 at clustering cells and estimating gene-gene covariance using both simulated and real scRNA-seq data,

281 An analysis of covariance was conducted to evaluate the impact of retin

282 Analysis of covariance was performed on the 6-month change in systol

283 This cerebellocerebral structural covariance was strongest in SZ, suggesting common underl

284 Analysis of covariance was used to examine changes in health status

285 ince genetic drift does not lead to temporal covariance, we can use these covariances to estimate wha

286 By performing multivariate analysis of covariance, we identified significant associations of th

287 background of positive genome-wide temporal covariances, we also identify signals of negative tempor

288 We used analysis of covariance while controlling for baseline values to exam

289 -Meier analysis and analyses of variance and covariance with ApoE4 status and age as covariates.

290 ying SSA to estimate C turnover time and its covariance with climate as well as ecosystem C sequestra

291 rowth reducing tree lifespan, and not due to covariance with climate or environment.

292 horoid plexus familiality and choroid plexus covariance with clinical, cognitive, brain, and peripher

293 All results survived after covariance with cognitive status measures, suggesting th

294 y-two chemicals were significantly linked by covariance with expressed genes.

295 inter-trial variance of eye position and its covariance with eye end position were evaluated.

296 VH and RBD shared a positive covariance with metabolism in the medial temporal lobe,

297 Analysis of covariance with planned contrasts showed no differences

298 Using linear regressions and analyses of covariance with post hoc Tukey-Kramer tests to compare s

299 Within this optimal family are covariances with "differential correlations", which are

300 Stochastic variance and covariance would similarly require major adjustment to a