ライフサイエンスコーパス: statistical

1 e show that the proposed model surpasses the statistical accuracy of the Galton-Watson model, which i

2 er); and (4) drugs that may have resulted in statistical alerts due to their correlation with drugs t

3 We developed a statistical AMPA-receptor-tetramer model, which permits

4 Interestingly, multivariate statistical analyses carried out only on extracted HRMS

5 Statistical analyses considering repeated events or even

6 Statistical analyses estimated the treatment delay times

7 sed tree metrics make it possible to conduct statistical analyses of ranked tree shapes and timed ran

8 Here, using mathematical modeling and statistical analyses of T cell receptor sequencing data,

9 Statistical analyses of these data reveal clusters that

10 e applied to other domains where large-scale statistical analyses over encrypted data are needed.

11 Results: Statistical analyses revealed no evidence of significant

12 We used multidimensional statistical analyses to characterize the impact of age o

13 Statistical analyses were carried out with ANOVA and mul

14 Statistical analyses were performed using non-parametric

15 Statistical analyses were performed with P < 0.05 as sig

16 A Cox regression model was used for statistical analyses.

17 linear discriminant, and k-nearest neighbor statistical analyses.

18 Low numbers of observations limit statistical analyses.

19 The statistical analysis (descriptive, sequence pattern anal

20 Descriptive statistical analysis and multiple logistic regression we

21 takes ~2 h to complete, from installation to statistical analysis and visualization, for a dataset of

22 The statistical analysis confirms that enzymes significantly

23 Statistical analysis disclosed a stochastic deterministi

24 Statistical analysis employed a 2 (Treatment Arm) X 3 (T

25 The statistical analysis estimates the relative risk of the

26 Our statistical analysis found that an additional 100 upwind

27 visualization tightly with state-of-the-art statistical analysis framework.

28 ing for future applications of the dynamical statistical analysis in exercise physiology and cardiolo

29 Statistical analysis included paired-sample t test, Cox

30 Statistical analysis included the paired t test and odds

31 Multivariate statistical analysis indicated that Psidium guajava L. (

32 Our statistical analysis of 11 mobility issues in the survey

33 classification scheme derived from in-depth statistical analysis of a large multinational patient co

34 In the statistical analysis of genome-wide association data, it

35 Moreover, statistical analysis of historic eruption occurrence sug

36 ion of the pile-up approach that can aid the statistical analysis of looping interactions.

37 R language has been used for the statistical analysis of radon time series (RTS) data.

38 n order to develop a systematic tool for the statistical analysis of such hypergraph, we propose a ge

39 Statistical analysis of the nonlinear behavior encoded i

40 Univariate and multivariate statistical analysis overlap identified haptoglobin-rela

41 i.e. biological) process and the form of the statistical analysis produce major conceptual and operat

42 Multivariate statistical analysis revealed 15 significant differentia

43 Statistical analysis revealed significant differences in

44 The statistical analysis showed significant differences betw

45 e number of genuine replicates, and when the statistical analysis treats all data points as independe

46 Statistical analysis was carried out using multiple line

47 The statistical analysis was conducted with multivariable li

48 Statistical analysis was performed on volatiles, quality

49 Though advanced statistical analysis was used more commonly in high-impa

50 s well as improvements in search algorithms, statistical analysis, and computational cost to achieve

51 procedure selection, duration of follow-up, statistical analysis, and publication requirements regar

52 Off-sample ion images confound and hinder statistical analysis, metabolite identification and down

53 s, predicted outcomes are used in subsequent statistical analysis, often without accounting for the d

54 mp experiments, in combination with advanced statistical analysis, to show that octanoyl-CoA binding

55 In addition, we conducted a statistical analysis, together with a graphical investig

56 Using advanced multivariate statistical analysis, we also showed that qPCR-negative

57 ions of forest lands along with multivariate statistical analysis, we found that there were significa

58 Regression modelling was used for a statistical analysis.

59 ere masked to patient allocation until after statistical analysis.

60 A random-effects model was used for statistical analysis.

61 alculated a stimulation map using voxel-wise statistical analysis.

62 ble working correlation matrix were used for statistical analysis.

63 and quantification, data normalisation, and statistical analysis.

64 index, in addition to a joint histogram for statistical analysis.

65 yses and in breeding schemes poses important statistical and computational challenges.

66 To this end, several statistical and machine learning methods have been propo

67 Cheminformatics, together with a "logical" statistical and machine learning-based approach, identif

68 limate change have been simulated using both statistical and process-based models.

69 mitation, here we employ a new nonparametric statistical approach based on analog forecasting, called

70 Formula: see text]-statistics to formulate a statistical approach for epidemiological analysis.

71 In summary, we introduce a novel statistical approach to systematically evaluate deleteri

72 s (CFD) using Inter-method reliability (IMR) statistical approach.

73 el to explain the data, quantified in modern statistical approaches by the likelihood function.

74 entropy models present an important class of statistical approaches for addressing this problem.

75 We used five different statistical approaches for data analysis.

76 Statistical approaches for dealing with missing data wer

77 both spatial and social data, and we outline statistical approaches that can control for and estimate

78 ent algorithms use a variety of semantic and statistical approaches to prioritize the typically long

79 ompartmental, to point-neuron, to population-statistical approaches.

80 vestigate spatial uniformity of FTE advance, statistical associations with 20th century climate trend

81 ompared with filtered back projection (FBP), statistical-based iterative reconstruction (SBIR), and m

82 We anticipate that existing statistical comparative approaches will be more commonly

83 encing with an analysis pipeline that allows statistical comparisons between different conditions, we

84 No statistical comparisons between groups were planned.

85 d even in those that do, well-powered direct statistical comparisons for sex as an independent variab

86 p-by-step commented R code (R Foundation for Statistical Computing, Vienna, Austria) in an effort to

87 n comparison to their analogs generated from statistical copolymers.

88 There was a statistical correlation between lead toxicity and abdomi

89 Here, we apply a global coevolution method, statistical coupling analysis (SCA), to identify coevolv

90 nders identified using clinical judgment and statistical criteria.

91 ch streams by using not only grammatical and statistical cues but also their prior knowledge of the f

92 Multivariate statistical data analysis indicated that the metabolic p

93 Graphpad Prism software was used for statistical data.

94 d trial (RCT) has enough power to detect any statistical differences between two groups while not ove

95 Among individual complications, there no statistical differences in intraabdominal leak, unplanne

96 However, no statistical differences in VA were observed between the

97 o do not assume that the data follow certain statistical distributions.

98 dynamics while applying delta-correction and statistical downscaling to calibrate measurements and pr

99 The statistical EcoToxModules were identified using co-expre

100 custom gene sets, called the functional and statistical EcoToxModules, in fathead minnow (Pimephales

101 , yielding predictable switching because the statistical ensemble behavior of oxygen vacancy defects

102 5 (Cohen d effect size) were performed, with statistical equivalence considered at P < .05.

103 on of results and are a prerequisite for the statistical evaluation of experimental outcomes.

104 A paired test was used for statistical evaluation.

105 ane rearrangement of benzobarrelene fit with statistical expectations from heavy-atom tunneling when

106 Statistical feature extraction was combined with princip

107 pression using both gene- and cell-dependent statistical features.

108 Despite unquestionable statistical foundations, this method has drawbacks, incl

109 Here we provide a statistical framework for assessing heritability models

110 Here, we use a flexible statistical framework for integrating multiple surveilla

111 Direct-coupling analysis (DCA) is a statistical framework that captures residue coevolution

112 A novel mathematical-statistical framework that included EAs with zero observ

113 nal/conjunctional false discovery rate (FDR) statistical framework that increases power of discovery

114 We developed LeafCutterMD, a new statistical framework that significantly improves the pr

115 We describe the statistical frameworks that incorporate and adjudicate b

116 We report the first example of a statistical gamma work distribution applied to single mo

117 tware solutions lack the raw performance and statistical grounding to efficiently handle the numerous

118 ld potentially improve power while retaining statistical guarantees, especially those that enable exp

119 r F-M than M-F transmission with substantial statistical heterogeneity across studies.

120 Galbraith plot was used to investigate statistical heterogeneity amongst studies.

121 omising new data type for the application of statistical indicators.

122 tically corrects for covariates, and permits statistical inference and penalized regression.

123 Sound principles of statistical inference dictate that uncertainty shapes le

124 his paper, we develop methods for correcting statistical inference using outcomes predicted with arbi

125 For statistical inference, a Bayesian hierarchical model is

126 tion and, making use of approximate Bayesian statistical inference, with experimental measurements ca

127 ent a method and software (HeIST) for making statistical inferences about the probability of hemiplas

128 sign and scale have been optimised to enable statistical inferences to be drawn.

129 We aimed to create models for statistical integration of allergen-specific IgE to pean

130 selection, and compound identification up to statistical interpretation.

131 ust then be determined to allow clinical and statistical interpretation.

132 The statistical law of the joint surface morphology at diffe

133 of human T cell dynamics compatible with the statistical laws of repertoire organization.

134 as responsible for this interference between statistical learning and episodic memory.

135 re, we examine the brain dynamics underlying statistical learning and inference in stable and volatil

136 Statistical learning and probabilistic prediction are fu

137 explicitly by behaviorally recording sensory statistical learning errors, and used dynamic causal mod

138 a provide compelling support for the role of statistical learning in vocal production learning and id

139 We demonstrate the use of modern statistical learning methods to develop a data-driven he

140 Statistical learning of transition patterns between soun

141 i, makes a direct link between the fields of statistical learning on the one hand and either predicti

142 ing a possible mechanistic account of visual statistical learning.

143 lysis routines and optimising a multivariate statistical machine learning algorithm.

144 set of a depressive disorder (Diagnostic and Statistical Manual of Mental Disorders IV criteria) diag

145 equences, we suggest moving away from strict statistical measurements and instead use a compatibility

146 poke machine-learning approach, hierarchical statistical mechanical modeling (HSM), capable of accura

147 Here we show how to use statistical mechanics to construct operators able to fle

148 presence of correlations, using methods from statistical mechanics.

149 We used multivariable linear regression and statistical mediation analyses to determine whether and

150 We propose a robust statistical method that accurately estimates DNA contami

151 m to eliminate outliers, and then used Limma statistical method to determine differentially methylate

152 A systematic statistical method to identify and correct for such conf

153 The present study applies a statistical method to in vivo multichannel spike trains

154 Here we present a statistical method, SPARK, for identifying spatial expre

155 tantially, depending on the study design and statistical method.

156 kallisto and bustools, that utilizes robust statistical methods and fast, memory efficient algorithm

157 By applying newly developed statistical methods for ancestral recombination graph in

158 al network models, we show that contemporary statistical methods for functional brain imaging-includi

159 ecosystem by reusing the data structures and statistical methods powered by other Bioconductor packag

160 tility of SRD, optionally coupled with other statistical methods such as ANOVA, is demonstrated on al

161 The application of statistical methods to comparatively framed questions ab

162 s, we compare the ability of three different statistical methods to identify remote earthquake trigge

163 In addition, rigorous statistical methods to perform differential expression (

164 Advanced statistical methods were applied to expose any relevant

165 Standard statistical methods were carried out to investigate the

166 Standards for choosing statistical methods with regard to well-calibrated proba

167 supervised and supervised learning and other statistical methods.

168 m of identifying epistasis demands efficient statistical methods.

169 Here, we describe a statistical model approach to reliably transform passive

170 propose, for the first time, the use of the Statistical Model Checking Engine (SMCE), a probability-

171 Our statistical model estimates that culture-confirmed cases

172 A uniform statistical model explains 34% of these shared variants;

173 ficient alkenes to develop a three-parameter statistical model relating enantioselectivity to physica

174 A statistical model represents a hypothesis about the unde

175 Fitting a statistical model to data from studies of influenza vacc

176 The statistical model used here provides a robust framework

177 Using a statistical model, we estimated the emergence date and s

178 ass spectrometry imaging in conjunction with statistical modeling allows discrimination of renal tumo

179 investigated by a combined experimental and statistical modeling approach.

180 Through statistical modeling that combines individual genetic an

181 that integrates dimensionality reduction and statistical modeling to grapple with the heterogeneity.

182 Statistical modeling, however, indicates that the FTSJ3

183 most of them, however, are based on complex statistical models and handle the multi-class case in an

184 aim of building and evaluating multivariate statistical models and machine learning methods for the

185 The SM has deep connections with parametric statistical models and the theory of phase transitions i

186 Statistical models applied to Year-3 data could help pre

187 prediction have been developed, among which statistical models approximating ENSO evolution by linea

188 Multivariable statistical models demonstrated age-related differences

189 We developed statistical models for completed cohort fertility at age

190 PAIRADISE outperforms alternative statistical models in simulation studies.

191 y factor associated with fine-root traits in statistical models including mycorrhizal association and

192 Cox, logistic, or linear statistical models were used depending on the outcome st

193 cycle data) in a semiblinded fashion, using statistical models, 25 mug/kg BW/d BPA [BPA(25)], or 250

194 in the state of Nebraska, USA, combined with statistical models, to quantify the contribution of cool

195 based early-warning signals (EWS), which are statistical moments estimated from time series data.

196 However, an adequate sample size as a statistical necessity for radiomics studies is often dif

197 Using a statistical nonlinear dimensionality reduction technique

198 We note that 2016 was a statistical outlier.

199 Data analysis was done using Statistical Package for Social Sciences software version

200 combines optimal mass transport theory with statistical pattern recognition.

201 Statistical phylogenetic methods are often used to model

202 Recently, statistical physics models called Potts models have been

203 that of classical mechanics, fluid physics, statistical physics, astrophysics, quantum physics and g

204 odels and the theory of phase transitions in statistical physics.

205 he parallel deforestation process adopting a statistical point of view.

206 ary assemblies (binders/nonbinders) based on statistical potentials.

207 lated interactions are embodied in classical statistical potentials.

208 We also provide a statistical power analysis, which shows that, in specifi

209 With an 80% statistical power and a type I error probability of 0.1,

210 ntly occur in multi-omics studies, weakening statistical power and risking false findings.

211 ree goals at the same time: (i) increase the statistical power by substantially reducing the burden o

212 reased in rats treated with rTM although the statistical power for this was low because of the small

213 By using tools to improve statistical power in combination with orthogonal analyse

214 anscriptomic data to showcase their improved statistical power of identifying gene-trait associations

215 y flattened average approach provides higher statistical power than Fieldtrip cluster inference.

216 To increase statistical power to identify genes associated with comp

217 lar disorder and schizophrenia would enhance statistical power to identify novel genetic loci for dep

218 myocardial infarction, but the trial lacked statistical power to show a difference in MACE.

219 Statistical power was enhanced by adding 1959 external c

220 to 2 weeks after the final dose; to maximize statistical power, we evaluated this end point in the pl

221 observations were not supported by adequate statistical power.

222 separate studies, many of which had limited statistical power.

223 iple clinical or genomic studies to increase statistical powers and ensure robust and accurate conclu

224 arning model, as well as accurately produces statistical predictions of the size effects in samples o

225 three classification algorithms and rigorous statistical procedure on one of the largest datasets ava

226 ion bias, imprecise theories, and inadequate statistical procedures.

227 luation overwhelmingly relies on inferential statistical procedures.

228 sets mimic real datasets by preserving their statistical properties and the relationships between var

229 We describe the statistical properties of alternative analyses with such

230 relationship between local dynamics and the statistical properties of network topology.

231 ly, this is done via hypothesis testing: the statistical properties of the empirical time series are

232 of a random process more likely reflects the statistical properties of the undergoing process compare

233 pairs, that often possess similar stationary statistical properties, as expected from aggregate sampl

234 Our results also validate statistical randomness as an unexplored approach to real

235 As with most statistical regression methods, OK minimizes the number

236 versus low-exacerbation groups and then used statistical regression to compare this VDP threshold aga

237 nsitive to object relationships that reflect statistical regularities of the experienced environment.

238 nscious learning and exploitation of spatial statistical regularities; (1b) these mechanisms are impl

239 Here, we provide evidence that, after the statistical relations between words have been extracted,

240 A and FBA) in their efficiency, accuracy and statistical relevance to model angiogenesis patterns of

241 g task requires care, especially in terms of statistical reliability and experimental confounds.

242 Statistical, sample, and methodological heterogeneity wa

243 , evolutionary conservation and pre-computed statistical scores as the prior knowledge to assemble a

244 [Formula: see text]) was used to derive two statistical shape models using a principal component ana

245 r 8 outcomes), these findings would not meet statistical significance (all P > .003).

246 igher risk of HCC, although it did not reach statistical significance (hazard ratio: 2.07; 95% CI: 0.

247 but this increase didn't reach the level of statistical significance (P = 0.061).

248 RH group (8% vs. 3%), but it failed to reach statistical significance (P = 0.167).

249 top 12 NDD genes with damaging DNVs that met statistical significance after Bonferroni correction (PT

250 This benefit reached statistical significance at 12 days after randomization.

251 There was no statistical significance between AUCs for the macular pa

252 older than 40 years (2.50 +/- 1.00), with no statistical significance detected between the two groups

253 Secukinumab did not meet statistical significance for superiority versus adalimum

254 Superiority of IVIG to placebo reached statistical significance for the primary endpoint for al

255 Of 101 included trials, 12 met statistical significance for their main endpoint, five f

256 rcher degrees of freedom" aimed at obtaining statistical significance increases the likelihood of obt

257 the sample size for adequate power to detect statistical significance is a crucial step at the design

258 rall mediation effect are proposed and their statistical significance is estimated by permutation pro

259 ement regarding the direction, strength, and statistical significance of associations for all covaria

260 signed rank test was employed to compute the statistical significance of the improvement in performan

261 presentation of the standard deviations and statistical significance shown in Figure 6 which are not

262 rd deviations of the SSIM were reported, and statistical significance was determined by using the Wil

263 No statistical significance was found on the distance betwe

264 Similar patterns of variable statistical significance were present within sex and rac

265 offspring from the same parents to determine statistical significance, and it can leverage any black-

266 = 0.104), but the associations did not reach statistical significance.

267 0.02-1.61), although the HR failed to attain statistical significance.

268 with collagen amount and position with high statistical significance.

269 ed for all variables, and P < 0.05 indicated statistical significance.

270 each other and with structure, and estimates statistical significance.

271 st based on inter-point distance to evaluate statistical significance.

272 tance of the adaptability that is enabled by statistical similarity among RHP chains and of the modul

273 Here, we perform a statistical simulation-based study on MDLs (primarily op

274 on was collected and analyzed using Stata 12 statistical software.

275 fission is three, which provides sufficient statistical space for triplet excitons to separate and a

276 a standalone manner drastically improves the statistical specificity, reducing the number of false po

277 s a basic understanding of MATLAB to use the statistical spectroscopic tools and analytical skills to

278 g task in complex interacting systems, where statistical stability is often poor due to lack of stati

279 phenotypes has motivated the development of statistical strategies focused on combining myriad indiv

280 Prior information represents the long-term statistical structure of an environment.

281 rchical Bayesian inference about the world's statistical structure.

282 tment strategy met prespecified criteria for statistical superiority, precluding definitive conclusio

283 odes and succinct HTML report of informative statistical tables and plots.

284 Similar statistical techniques can be used to conduct a rigorous

285 s between diet and periodontitis using novel statistical techniques for dietary pattern analysis.

286 sformed titers were examined using different statistical techniques.

287 information divergency and (iii) a rigorous statistical test for the significance of all the identif

288 al disorders, and develop a simulation-based statistical test to identify gene-specific enrichment of

289 e, Antibody Sequence Analysis Pipeline using Statistical testing and Machine Learning (ASAP-SML), to

290 t be formally tested due to the prespecified statistical testing hierarchy.

291 ng profiles across single cells and performs statistical tests to compare percent spliced-in (PSI) va

292 Statistical tests were performed to confirm the quality

293 ished by UV-vis spectrometry and endorsed by statistical tests.

294 e evaluated with univariate and multivariate statistical tests.

295 To test this hypothesis, we developed a statistical-thermodynamics-based informatics framework,

296 e of a face image linearly increase with its statistical typicality (log likelihood).

297 In particular, it lacks assessment of statistical uncertainty and the ability to perform hypot

298 We describe SURF, Statistical Utility for RBP Functions, for integrative a

299 Statistical validation within the workflow included repe

300 es researchers to retrospectively assess the statistical validity of previously reported associations