ライフサイエンスコーパス: statistical test

1 etween the 2 treatment groups using a global statistical test.

2 d and statistically compared using McNemar's statistical test.

3 riminant functions and variables within each statistical test.

4 mation to contrast one or more networks in a statistical test.

5 me 9p21 for association using a gene-centric statistical test.

6 cted to PCA to provide an easy to understand statistical test.

7 following periodontal therapy using a single statistical test.

8 analyzed with the Spearman rank correlation statistical test.

9 they are different according to a particular statistical test.

10 classified as likely correct, using a simple statistical test.

11 worse outcomes and were analyzed by a global statistical test.

12 by appropriate non-parametric or parametric statistical tests.

13 on studies with a focus on study designs and statistical tests.

14 r cophylogenetic analyses, performing robust statistical tests.

15 M molecular subgroups by using nonparametric statistical tests.

16 rge-scale experimental data with a number of statistical tests.

17 n intention-to-treat basis using appropriate statistical tests.

18 ation, annotation, pathogenic prediction and statistical tests.

19 e evaluated for compartmentalization using 4 statistical tests.

20 3% (95% CI: 0%, 6%) they used inappropriate statistical tests.

21 d approach were evaluated through normalized statistical tests.

22 were compared with the actual outcomes using statistical tests.

23 however, present a challenge to traditional statistical tests.

24 revious outpatient therapy) using univariate statistical tests.

25 strategies were compared by using two-sided statistical tests.

26 r, but the NCA TFAs outperform regression in statistical tests.

27 per gene, which can result in low power for statistical tests.

28 ce of these models is judged using the usual statistical tests.

29 signal intensity decrease with nonparametric statistical tests.

30 ng and clustering motifs, and several useful statistical tests.

31 new LASSO method has the ability to perform statistical tests.

32 H cell-seeded scaffolds, using nonparametric statistical tests.

33 utation-based method for combining different statistical tests.

34 se of normally distributed data, parametric- statistical tests.

35 mean (+/- SD) and compared using appropriate statistical tests.

36 time by TG/DTA with application of different statistical tests.

37 sults may remain unidentified after applying statistical testing.

38 Data were tabulated for statistical testing.

39 nt number of cases with differences to allow statistical testing.

40 null hypotheses for further experimental and statistical testing.

41 nce index (MLCI) for influence on downstream statistical testing.

42 We compared a standard statistical test-a score test-with a recently developed

43 on algorithm combined with a two-dimensional statistical test allows the detection of DMRs in large m

44 jor updates in XBSeq2, including alternative statistical testing and parameter estimation method for

45 dom measurement error decreases the power of statistical tests and a review of the roles of sample si

46 The quality of LC-MS data is evaluated using statistical tests and alignment quality tests.

47 We present two-sided statistical tests and correct for multiple comparisons.

48 methods are based on a series of univariate statistical tests and do not properly account for the co

49 The method is based on rigorous statistical tests and does not require any presumed kine

50 Furthermore, the statistical tests and linear regression showed that the

51 We have performed a variety of statistical tests and present evidence that the cis-regu

52 ions show high levels of sensitivity for the statistical test, and application to a control normal-ti

53 ave uniform transmissibility through a novel statistical test, and find that certain strains appear m

54 ciated with SSI were tested using univariate statistical tests, and a hierarchical generalized linear

55 voxel-wise manner, resulting in around 10(5) statistical tests, and considerable emphasis placed on c

56 Application of the more stringent statistical tests applied to the normalized 2D DIGE data

57 Because all parameters required for the statistical test are estimated directly from the data, i

58 The statistical tests are based on the Erlang distribution m

59 Several statistical tests are proposed for a complete dissection

60 genetic epidemiology and argue for retaining statistical testing as an important part of the tool kit

61 Advanced comparative features comprise statistical tests as well as multidimensional scaling, h

62 Here, we present two statistical tests based on the distinctive spatial patte

63 However, we find that statistical tests based on these two models give conflic

64 A statistical test, based on the transformation of the exp

65 mlDNA substantially outperformed traditional statistical testing-based differential expression analys

66 We present a novel non-parametric statistical test between splice graphs to assess the sig

67 on by Buhaug is based on absent or incorrect statistical tests, both in model selection and in the co

68 Statistical testing by eating disorder categories with t

69 tion and evolution, we show that stratifying statistical tests by domain family yields excellent resu

70 Our statistical test can also include tree reconstruction in

71 sis testing problems-that is, those in which statistical tests can be partitioned naturally-controlli

72 Newly incorporated statistical tests cover a wide array of univariate analy

73 ous approaches such as DRME model based on a statistical test covering the IP samples only with 2 neg

74 ysis Testing), that can perform any sib pair statistical test currently in use, as well as any user-d

75 Based on a novel statistical test employing conjugate Fisher transformati

76 Our methods combine de novo assembly with statistical tests enabling motif discovery without the u

77 on coefficient, the higher is sensitivity of statistical testing, especially of the paired t-test.

78 The presented method conducts a statistical test for differential analysis in regions of

79 ependency DifferentialitY (EDDY), which is a statistical test for differential dependencies of a set

80 one analytics with novel feature extraction, statistical test for differential expression and diagnos

81 ling measurements separately, and performs a statistical test for differential translation efficiency

82 wback is that, because they perform just one statistical test for each individual experiment, they ma

83 re for relative abundance profiles, derive a statistical test for equality and propose a protein-leve

84 n favor of ART-123, which met the predefined statistical test for evidence suggestive of efficacy).

85 To develop a more powerful statistical test for genetic-association studies, we com

86 skal-Wallis test is a popular non-parametric statistical test for identifying expression quantitative

87 A statistical test for interaction between previous aborti

88 CoMEt includes an exact statistical test for mutual exclusivity and techniques t

89 We apply a statistical test for such LOH-influenced disruptions, an

90 strategy including irinotecan--satisfied the statistical test for superiority (p=0.01).

91 Statistical test for trend of the effect of hormone ther

92 ant trend on the BDI (beta = -1.14; P = .08, statistical test for trend), but no significant differen

93 To enable statistical testing for differences in mass signal inten

94 Statistical testing for differences in serum ghrelin lev

95 The noninferiority margin was 5 letters, and statistical testing for noninferiority was based on a 1-

96 Statistical testing for substantial differences in ghrel

97 ; if noninferiority was established, 2-sided statistical testing for superiority was conducted.

98 In this work, we develop much needed statistical tests for assessing the independence of the

99 d PubChem compound identifiers, and based on statistical tests for association.

100 Statistical tests for detecting mosaic structure or reco

101 prevalence rates, confidence intervals, and statistical tests for differences.

102 eference, counting transcript abundance, and statistical tests for differentially expressed genes.

103 a maximum-likelihood approach, we conducted statistical tests for evidence of codon sites where the

104 Current statistical tests for exclusivity that incorporate both

105 However, to date, formal statistical tests for gene-gene interaction on untyped S

106 Recently, frequentist statistical tests for Hardy-Weinberg equilibrium have be

107 ed to normalized read counts and enabled new statistical tests for identifying developmentally regula

108 We develop several statistical tests for identifying Significantly Mutated

109 shifts using ancestral protein resurrection, statistical tests for positive selection, forward and re

110 ining the best study design, sample size and statistical tests for sequence-based association studies

111 Statistical tests for the detection of differentially ex

112 rity since it was realised that the power of statistical tests for the study of evolutionary trends c

113 ogenes are utilized to construct appropriate statistical tests for the transposon insertion tolerance

114 We propose statistical tests for two important but different aspect

115 Classical statistical tests for within-sample comparisons fail as

116 models with features identified by different statistical tests further demonstrated the advantage of

117 Each type of statistical test has its own advantages in characterizin

118 Distance-based statistical tests have been applied to test the associat

119 Simple statistical tests have been devised to infer ongoing sel

120 Standard statistical tests have been used to verify that the geno

121 It is therefore surprising that rigorous statistical tests have failed to find evidence of positi

122 Statistical tests have shown that some cis-acting regula

123 Using rigorous statistical tests, here we characterize the relationship

124 Because of statistical testing hierarchical rules, the 50-mug patch

125 is using Cochran-Armitage and Fisher's exact statistical tests identified 1364 statistically signific

126 Statistical tests identified genes that exhibited differ

127 veloped as a two-part process involving: (1) statistical testing in order to determine the number of

128 he intervals are valid for most large-sample statistical tests in any context, and can be used in the

129 The BlueSNP R package implements GWAS statistical tests in the R programming language and exec

130 with the smallest P-values from appropriate statistical tests) in the training set also had the stro

131 Statistical testing included analysis of variance, t tes

132 Statistical testing included Kruskal-Wallis tests for co

133 Statistical testing included the intraclass correlation

134 Statistical tests included Spearman rho coefficients, re

135 a dependence kernel is sufficient to render statistical tests independent regardless of the level of

136 Two statistical tests indicate that both modeled and unmodel

137 Non-parametric statistical tests indicated that Markov models of order

138 tegrated copy number filtering, and to use a statistical test inherently robust for use in platforms

139 The statistical test involves a set of parameters that can b

140 A non-parametric statistical test is applied to each ASM to detect signif

141 in the probability distribution on which the statistical test is based, because of the differences in

142 can be considered to be flat and no further statistical testing is needed.

143 high-dimensional data, variable-by-variable statistical testing is often used to select variables wh

144 Combining P-values from multiple statistical tests is a common exercise in bioinformatics

145 Performing statistical tests is an important step in analyzing geno

146 an be detected using a collection of generic statistical tests known as early warning signals (EWSs).

147 Other statistical tests like student t-test and logistic regre

148 rain lifespan, after correction for multiple statistical testing (miR-203-3p [beta-coefficient = -0.6

149 By one statistical test, missense variants of KLF4 as a group w

150 More rigorous statistical tests must be used to account for such biase

151 We present a new statistical test of association between a trait and gene

152 Here, we describe a formal statistical test of colocalization and apply it to type

153 reement between such probe sets, utilizing a statistical test of concordance, Kendall's W coefficient

154 Based on the a priori statistical test of equivalence, placebo and high-dose t

155 ed a new mass spectrometry method, the STEP (statistical test of equivalent pathways) analysis that u

156 s of aggressive and antisocial behavior; and statistical test of genotype-environment interaction.

157 The second is to conduct a statistical test of the hypothesis that the gene is diff

158 Here we present a statistical test of the orbital forcing hypothesis, focu

159 A formal statistical test of the treatment-by-biomarker interacti

160 However, while statistical testing of differences in mean expression le

161 Through multiple-sequence alignment and statistical testing of each aligned amino acid, we ident

162 Sequential statistical testing of noninferiority (margin of 1.075),

163 ingenuity pathway analysis was performed for statistical testing of pathways.

164 A maize germplasm collection was used for statistical testing of the correlation between carotenoi

165 Statistical tests of average responses detected no signi

166 guide the development and interpretation of statistical tests of causality between phenotypes using

167 Maximum likelihood trees and statistical tests of compartmentalization revealed inter

168 Statistical tests of direct cause and effect relationshi

169 rtions of patients with elevated markers and statistical tests of elevations as prognostic factors.

170 tion error parameters) for two commonly used statistical tests of genetic association, the linear tre

171 if they are necessary, researchers should do statistical tests of interaction, rather than analyse ev

172 There are a number of polymorphism-based statistical tests of neutrality, but most of them focus

173 We performed statistical tests of phylogeographic structure and appli

174 hip also explains the similar performance of statistical tests of population-genetic models that rely

175 imony and Bayesian methods demonstrates that statistical tests of positive selection can be misleadin

176 kelihood based estimation further allows for statistical tests of several relevant hypotheses, includ

177 also provide a framework to enable rigorous statistical tests of significance in intervention studie

178 Statistical tests of the fit to the predictions of these

179 , these articles did not include analyses or statistical tests of the mortality data, and the 2 artic

180 confidence interval was achieved by standard statistical tests of the recovered probability density f

181 upertree of highest likelihood, and performs statistical tests of two or more supertrees.

182 ssociations can be identified using a simple statistical test on all paired combinations of genetic v

183 is a bioinformatics technique that performs statistical testing on biologically meaningful sets of g

184 data for one or more species; (ii) performs statistical tests on the integrated datasets; and (iii)

185 d pain response at 12 weeks) were to undergo statistical testing only if the primary end point analys

186 analysis has more power than the equivalent statistical test performed on a single large experiment.

187 The large number of statistical tests performed also makes sufficient type o

188 Statistical tests performed include Pearson correlation

189 The Pedigree Relationship Statistical Test (PREST) was used to identify pedigrees

190 counting for spatial correlations within the statistical testing procedure.

191 We develop four frequentist statistical test procedures for X-linked markers that ta

192 ee indices of dynamic interaction reliant on statistical testing procedures are susceptible to Type I

193 It utilizes a wide gamut of statistical tests, procedures, and methodologies that be

194 Statistical tests produced regression R2 values of 88%,

195 The non-parametric nature of our statistical test provides fast and efficient analyses, a

196 In contrast to available statistical tests, RareIBD generates accurate p values e

197 age approaches involving IBD have focused on statistical testing, rather than on the effect estimates

198 Various statistical tests rejected a neutral equilibrium model o

199 Furthermore, a variety of statistical tests show strong deviations from neutrality

200 n in preliminary data processing and optimal statistical testing significantly enhances the functiona

201 ne toxicity were analysed using a gene based statistical test (SKAT-O test).

202 Our statistical testing strategy showed no significant evide

203 The necessary parameters for statistical tests (such as the expected frequency of rep

204 Standard statistical tests, such as the t-test are not suited for

205 Statistical test suggested simulated results were not si

206 n dynamic displays alongside user-controlled statistical tests, supporting rapid statistical validati

207 Statistical test (t-student) was applied to the coeffici

208 method for detecting nonneutral evolution, a statistical test that can identify sites that are unusua

209 This assessment uses a novel statistical test that extends the widely used Hypergeome

210 cts on deglaciation are overcome using a new statistical test that focuses on maxima in orbital forci

211 It supports any statistical test that is based on contingency tables, an

212 terion specifies a single, information-based statistical test that is free from ad hoc parameters and

213 noprecipitation-sequencing (ChIP-seq) with a statistical test that simultaneously scores peak height

214 ropose a combination of machine learning and statistical testing that takes correlation structures wi

215 stant seasonality, thus confirming by formal statistical testing that the magnitude of the seasonalit

216 Effect sizes were calculated from statistical tests that could be converted to standardize

217 dies, having >1 outcome variable, conducting statistical tests that produce >1 P value, taking multip

218 We propose a distance-based statistical test, the generalized RV (GRV) test, to asse

219 For a variety of magnitude cutoffs and three statistical tests, the global catalog, with local cluste

220 s in a bayesian analysis may provide a novel statistical test to assess the consistency of species ab

221 Using this analysis method, we formulated a statistical test to compare the ACO hypothesis with meas

222 ly, we use a recently devised non-parametric statistical test to demonstrate that PPI networks of man

223 Y (Evaluation of Differential DependencY), a statistical test to detect differential statistical depe

224 In this article, we propose a new statistical test to detect differentially methylated loc

225 We present a statistical test to detect that a presented state of a r

226 analysis by weighting the likelihood of each statistical test to reflect the number of putative causa

227 ch other and one is selected as best without statistical testing to determine whether the improvement

228 Here, we propose a suite of statistical tests to address these open needs: a paramet

229 SADMAMA implements two types of statistical tests to answer this question: one type is b

230 ase of supernovae so we can perform rigorous statistical tests to check whether these 'standardisable

231 It is therefore important to use robust statistical tests to decipher the correct theoretical mo

232 We designed statistical tests to detect AEI in a comprehensive set o

233 ncreasing need to develop and apply powerful statistical tests to detect association between multiple

234 in genotype versus sequence data or power of statistical tests to detect selection in different time

235 ents, which has made it difficult to develop statistical tests to either confirm or deny putative tra

236 nt scenarios, (ii) using a sequence of three statistical tests to eliminate background regions and to

237 This algorithm employs straightforward statistical tests to evaluate the significance of differ

238 tion pressure upon the cancer samples, exact statistical tests to examine this problem are devised.

239 umor genome data could complement gene-based statistical tests to identify likely new cancer genes; b

240 The method uses correlation analysis and statistical tests to identify network modules by three c

241 nologies have motivated development of novel statistical tests to identify rare genetic variation tha

242 es used weights and complex design-corrected statistical tests to infer generalizability to the US po

243 s introduced to select and apply appropriate statistical tests to loadings plot data, which are then

244 atlas comparison was performed via per-voxel statistical tests to localize shape differences (signifi

245 We apply the GP growth model and develop statistical tests to quantify the differential effects o

246 ematically combine information from multiple statistical tests to rigorously evaluate a single overar

247 he statistics module recommends and performs statistical tests to suggest biological areas that are i

248 get associations using one of three separate statistical tests, to link microRNA targets to functiona

249 t formulae to calculate the power of various statistical tests under different strategies for pooling

250 ion test (SKAT) is probably the most popular statistical test used in rare-variant association studie

251 Statistical tests used in the analysis were all two-side

252 Statistical tests used the factorial design and included

253 We performed statistical testing using FBAT-CNV.

254 Two-sided statistical tests using conditional logistic regression

255 Statistical tests using genome-wide alignments of eight

256 A global statistical test was used to analyze the 9 scales of the

257 Statistical testing was performed by using linear regres

258 Nonparametric statistical testing was performed on all comparisons.

259 Statistical testing was performed with Wilcoxon's rank s

260 Using the same statistical test, we found 1495 genes whose expression w

261 Using statistical tests, we identified a small number of cases

262 Using two statistical tests, we identified eight candidate genes.

263 All statistical tests were 2 sided.

264 vitamin E, vitamin C, and carotenoid intake; statistical tests were 2-sided.

265 All statistical tests were 2-sided.

266 Statistical tests were 2-sided.

267 All statistical tests were 2-sided.

268 All statistical tests were 2-sided.

269 Statistical tests were applied for data analysis.

270 Standard quality control and statistical tests were applied to the 1000 Genomes imput

271 Machine learning feature selection and statistical tests were combined to identify candidate bi

272 Both chromosome-wide and genome-wide statistical tests were conducted to identify imprinted q

273 Statistical tests were performed on EEG and NIRS signals

274 Appropriate statistical tests were performed to evaluate measured qu

275 Statistical tests were performed using Wilcoxon signed-r

276 All statistical tests were two sided and unadjusted for mult

277 The statistical tests were two sided, with a type-I error se

278 All statistical tests were two sided.

279 tive risks and 95% confidence intervals; all statistical tests were two sided.

280 All statistical tests were two sided.

281 All statistical tests were two sided.

282 All statistical tests were two-sided.

283 All statistical tests were two-sided.

284 ere estimated using logistic regression, and statistical tests were two-sided.

285 All statistical tests were two-sided.

286 Statistical tests were two-sided.

287 All statistical tests were two-sided.

288 All statistical tests were two-sided.

289 Non-parametric statistical tests were used for between-group comparison

290 Statistical tests were used to assess changes in the cli

291 Statistical tests were used to assess correlations betwe

292 Multivariate statistical tests were used to assess effectiveness with

293 Non-parametrical statistical tests were used.

294 Standard two-sided statistical tests were utilized.

295 Kolomogov-Smirnov statistical tests, which compare the distributions of en

296 n the flipped analysis and by non-parametric statistical testing (whole brain corrected P-value < 0.0

297 analysed the primary endpoint with one-sided statistical testing with calculation of upper 95% confid

298 a-particle tracks per cell were subjected to statistical tests with Poisson, LN, and Poisson-lognorma

299 M2, and ERN1) by applying between population statistical tests (XP-EHH and XP-CLR).

300 The global statistical test yielded t1865.8 = -0.75 (2-sided P = .4