ライフサイエンスコーパス: statistical method

1 the population activity space using a novel statistical method.

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

3 supervised and supervised learning and other statistical methods.

4 We employed and compared with three statistical methods.

5 with larger training datasets and innovative statistical methods.

6 hould extend beyond 7 d and use time-varying statistical methods.

7 easures of hand function using 2 independent statistical methods.

8 erties that distinguish it from better-known statistical methods.

9 m of identifying epistasis demands efficient statistical methods.

10 variants were misclassified by conventional statistical methods.

11 the current UK PNF criteria and is based on statistical methods.

12 s using cross-population (XP-EHH and XP-CLR) statistical methods.

13 es heavy-duty computational tools, and novel statistical methods.

14 immune mediators were analyzed using various statistical methods.

15 are based on clinical experience rather than statistical methods.

16 atically examined due to a lack of available statistical methods.

17 yses with dense marker panel data and recent statistical methods.

18 raft thickness, and 8 studies used different statistical methods.

19 medical data may hinder the use of classical statistical methods.

20 hich brings challenges to the development of statistical methods.

21 n-automated" ML approach as well as standard statistical methods.

22 ortex and medulla samples using multivariate statistical methods.

23 nformatics approaches alongside conventional statistical methods.

24 al clearance were explored using appropriate statistical methods.

25 e importance of the appropriate selection of statistical methods.

26 easures, spatial replication and extent, and statistical methods.

27 reasonably be drawn from that data using new statistical methods.

28 s the development of novel and more powerful statistical methods.

29 We apply a statistical method(15,16) to quantify the evolutionary t

30 of this study is the application of a novel statistical method accounting for censoring in the follo

31 The introduction of multivariate statistical methods allows investigators to utilize data

32 We develop TimeMeter, a statistical method and tool to assess temporal gene expr

33 We develop statistical methods and an R package SummaryAUC for appr

34 n of mild iodine deficiency, with a focus on statistical methods and approaches.

35 Using phylogenetic statistical methods and biophysical models combined with

36 le approach facilitates the dissemination of statistical methods and codes to independent researchers

37 rriers in advancing the development of novel statistical methods and computational algorithms for gen

38 There is a need to develop efficient statistical methods and computational algorithms to cons

39 te the rapid advances in technologies, novel statistical methods and computational tools for analyzin

40 ude 7 studies (815 eyes) that used different statistical methods and did not find significant associa

41 We used both statistical methods and dynamic mathematical models to (

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

43 ALS is robust with respect to the choice of statistical methods and is validated through extensive s

44 Using statistical methods and Kernel Logistic Regression (KLR)

45 Using classical statistical methods and machine learning to combine ChIP

46 d cell types, recent work employing unbiased statistical methods and more diverse tasks reveals unsus

47 Descriptive statistical methods and multilevel linear regression mod

48 he long-term benefits were coherent by all 3 statistical methods and persisted among patient subgroup

49 cover distortions of conclusions produced by statistical methods and psychosocial forces.

50 s so by exploiting concepts from traditional statistical methods and recent fair machine learning sch

51 rkflow management, as well as improvement in statistical methods and study design, there have been gr

52 mmarize 3 GAW19 contributions applying novel statistical methods and testing previously proposed tech

53 the misapplication and misinterpretation of statistical methods and tests are long-standing and wide

54 The statistical methods and the KLR models both show that cy

55 from reference data sets using multivariate statistical methods and the subsequent classification of

56 The statistical methods and their implementations in NBZIMM

57 We compare multiple statistical methods and use simulations to investigate t

58 tistic identified as a cue, differed between statistical methods and with respect to the time span of

59 ativity and ability to collaborate and lead, statistical methods, and study design.

60 ubstantial clinical heterogeneity, differing statistical methods, and variable methodological quality

61 in 3 methodologic domains ("study design," "statistical methods," and "reporting methods") were asse

62 Here, we introduce a novel statistical method, annotation-assisted isoform discover

63 s to evaluate the effectiveness of different statistical methods applied for urinary proteomic biomar

64 es (SVM) and artificial neuron network (ANN) statistical methods applied to the spectroscopic data al

65 Statistical methods are developed and implemented for de

66 Statistical methods are implemented for treating outlier

67 Conventional statistical methods are less than ideal because they eit

68 nstrained data become inappropriate, and new statistical methods are needed to analyze this special t

69 generated from high-throughput experiments, statistical methods are often too simplistic to understa

70 y approach to catalyst optimization in which statistical methods are used at each stage to streamline

71 Statistical methods are used to accommodate possible err

72 Here we develop a statistical method based on characteristics known to inf

73 Here, we adjusted a statistical method based on genetic data to predict, for

74 We have developed a novel statistical method based on summarizing sequenced reads

75 gh specific density feedbacks, and show that statistical methods based on model averaging provide rel

76 power to identify risk variants compared to statistical methods based on smaller number of GWAS data

77 ology around a core set of study designs and statistical methods bearing little resemblance to the ch

78 alculation, and 46 (38.7%) chose appropriate statistical methods, both accounting for the correlation

79 We develop a novel and robust statistical method-called SCmut-to identify specific cel

80 ations in scRNA-seq data, such that existing statistical methods can be improved.

81 -up should be considered so that appropriate statistical methods can be incorporated into the design.

82 infrared spectra and the use of multivariate statistical methods can be useful for studying the compo

83 Standard statistical methods can have difficulty learning discret

84 fore analyzing compounds through modeling or statistical methods, chemical features need to be tracke

85 We developed a novel statistical method, ChromNet, to infer a network of thes

86 d the ensemble utilize (1) a self-correcting statistical method combining influenza-related Google se

87 Our statistical methods controlled for temporal patterns in

88 Applying multiple statistical methods could emphasize the multiple facets

89 However, many statistical methods currently used to analyse short time

90 bias has not previously been highlighted and statistical methods designed to minimize such biases hav

91 vide thorough reviews and discussions on the statistical method developments and data analysis strate

92 Here we present an efficient, flexible statistical method, diCal2, that can use whole-genome se

93 tools, but applying scoring procedures with statistical methods does not eliminate the fundamental p

94 We develop a statistical method, epiG, to infer and differentiate bet

95 Existing statistical methods extract insufficient information fro

96 Here we propose a novel statistical method, finding batch effect (findBATCH), to

97 Here, we describe a new statistical method for calling cells from droplet-based

98 hus, there is an acute need for an objective statistical method for classifying whether an experiment

99 r to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare

100 We developed Monovar, a statistical method for detecting and genotyping single-n

101 We present a statistical method for determining whether phenotypicall

102 q-value is a widely used statistical method for estimating false discovery rate (

103 In this paper, we introduce a novel statistical method for identifying genes with significan

104 We present EVmutation, an unsupervised statistical method for predicting the effects of mutatio

105 We proposed a statistical method for the conservative adjustment of q-

106 Employing a novel statistical method for the study of the health effects o

107 Novel statistical method for Tn-seq data analysis is needed to

108 opical principal component analysis (PCA), a statistical method for visualization and dimensionality

109 he Dashboard is complementary to traditional statistical methods for analysis of gene-expression data

110 g and visualization, and implements multiple statistical methods for analysis of these data.

111 We introduce new statistical methods for analyzing genomic data sets that

112 Statistical methods for analyzing such datasets are scar

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

114 Here we use statistical methods for causal inference to investigate

115 Statistical methods for CNV association analysis can be

116 Recent developments in statistical methods for computation of direct evolutiona

117 predictive ability of five commonly applied statistical methods for cue identification (absolute and

118 re subsequently evaluated using multivariate statistical methods for dimension reduction and results

119 th codes) and small area estimation methods (statistical methods for estimating rates in small subpop

120 spectrum match scores exist, the field lacks statistical methods for estimating the false discovery r

121 al development of the underlying models, and statistical methods for estimating their parameters from

122 TopDom, to identify TDs, along with a set of statistical methods for evaluating their quality.

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

124 omplete code and illustrations of new sparse statistical methods for high-dimensional, longitudinal m

125 igm and limiting the application of existing statistical methods for networks.

126 n any one of these traits, but the necessary statistical methods for obtaining risk estimates are lac

127 ring, comparing the results from an array of statistical methods for optimal causal inference.

128 asuring, and dealing with heterogeneity; and statistical methods for pooling results.

129 statistical methods, identifying appropriate statistical methods for PRO analysis, standardising stat

130 The commonly used statistical methods for RNA-seq differential expression

131 quality control procedure and development of statistical methods for RNA-seq downstream analyses.

132 e sequencing (WGS) technology, more advanced statistical methods for testing genetic association with

133 However, related statistical methods for testing SNP-SNP interactions are

134 We present a set of statistical methods for the analysis of DNA methylation

135 t populations to which these OPC apply, and (statistical) methods for OPC development.

136 During the past few years, various novel statistical methods have been developed for fine-mapping

137 However, only few statistical methods have been developed so far for estim

138 Although several statistical methods have been developed to control for p

139 Statistical methods have been developed to determine whe

140 Recently, several statistical methods have been developed to improve stati

141 cal and accessible, detailed descriptions of statistical methods have been omitted.

142 Although several statistical methods have been proposed, they either requ

143 Several statistical methods have been recently proposed to impro

144 Various statistical methods have been used in order to get the m

145 Advances in sequencing techniques and statistical methods have made it possible not only to pr

146 cians and unearth associations that previous statistical methods have not found.

147 ectives that can be matched with appropriate statistical methods, identifying appropriate statistical

148 earchers may be reluctant to use appropriate statistical methods if their hypothesis is about the pse

149 Here, we develop a statistical method, IMAGE, for mQTL mapping in sequencin

150 n analysis appears as the most commonly used statistical method in the area.

151 or epilepsy syndromes, and was robust across statistical methods in all families and in generalized f

152 ative analysis of genomic data that includes statistical methods in combination with visual explorati

153 Using statistical methods in evenly split development and vali

154 complex traits exemplifies the importance of statistical methods in genetics.

155 Most conventional statistical methods in GWAS only investigate one phenoty

156 Statistical methods included discrete-time survival anal

157 thylated CpGs between groups using different statistical methods including Fisher's Exact Test, Stude

158 over discrete timepoints were combined with statistical methods including the following longitudinal

159 Then we applied refined statistical methods, including some based on exomic hapl

160 The statistical methods introduced here reduce discrepancies

161 The progressive coverage statistical method is introduced to provide the sufficie

162 However, currently available statistical methods lack power in detecting differential

163 Statistical methods leveraging the tissue-specificity of

164 To address these issues we developed a statistical method, LinTIMaT, which reconstructs cell li

165 We used standard statistical methods (logistic regression) as well as the

166 ogical information, the results of different statistical methods may best be combined into a master p

167 Previously, we developed a statistical method, minimum probability flow-Boltzmann M

168 A secondary aim was to test if the statistical method of elastic net regularization would i

169 Easy-HLA implements a computational and statistical method of HLA haplotypes inference based on

170 The statistical method of random uncertainties has been adop

171 d +/-1.00 D; and interquartile displays) and statistical methods of analyses.

172 g and variable selection methods and finally statistical methods of analysis and validation.

173 onite fossil record is commonly used to test statistical methods of evaluating mass extinctions to ac

174 In this article, we review recent statistical methods of extracting biophysical parameters

175 nd-pathway associations compared to existing statistical methods of pathway enrichment analysis.

176 However, statistical methods often treat cellular heterogeneity a

177 and CUSUM+, a version of the cumulative sum statistical method optimized for longer events that do.

178 We have developed a novel statistical method, Phantom, to investigate gene set het

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

180 The results were processed using two statistical methods - principal component analysis (PCA)

181 most of this difference disappears, and the statistical methods produce similar results.

182 The development of sequencing techniques and statistical methods provides great opportunities for ide

183 average expression of a biomarker, standard statistical methods require that variance be approximate

184 mputationally scalable and widely applicable statistical method (SEER) for the identification of sequ

185 Much previous research has relied on statistical methods, separately, to address two problems

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

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

188 For other multivariate statistical methods such as canonical correlation analys

189 Statistical methods such as machine learning and Cox reg

190 Simpler, traditional statistical methods such as ridge regression can outperf

191 The study used several statistical methods tailored to address the age at onset

192 s self-contained multivariate non-parametric statistical methods testing a complex null hypothesis ag

193 imized prion amplification procedures with a statistical method that accounts for false-positive and

194 We developed a statistical method that accounts for subtle changes in t

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

196 Mendelian randomization (MR) is a statistical method that can be used to investigate the c

197 We propose a statistical method that can detect not only genes that s

198 We provide a statistical method that clusters the solutions to furthe

199 Here we adopt an alternative statistical method that substitutes space for time to es

200 In this article, we propose a new statistical method that will infer likely upstream regul

201 We introduce a novel statistical method that, by focusing on individuals, ena

202 conditions, suggesting the need for flexible statistical methods that are able to cope with unbalance

203 Scasat treats the data as binary and applies statistical methods that are especially suitable for bin

204 ife scenario in all populations, needing new statistical methods that can assess their complex effect

205 Thus, new statistical methods that can control for population stra

206 Statistical methods that can integrate such multimodal d

207 quencing studies requires the development of statistical methods that can properly account for the co

208 Multivariate statistical methods that combine information from all bi

209 Statistical methods that control the false discovery rat

210 data were analyzed using recently developed statistical methods that demonstrate improvements over c

211 nance imaging (fMRI) analyses use parametric statistical methods that depend on a variety of assumpti

212 ality measurement network, we present simple statistical methods that do not require extensive traini

213 hesis and their findings are very promising, statistical methods that effectively harness multilayere

214 There are many statistical methods that either summarize gene-level sta

215 Although statistical methods that have been developed for microar

216 It outperforms several statistical methods that have been widely used to study

217 d straightforward application of traditional statistical methods that ignore this two-way dependence

218 With this motivation, several statistical methods that jointly analyze multiple phenot

219 Here, we review recent progress on statistical methods that leverage summary association da

220 n of these data requires unbiased, efficient statistical methods that model the dynamics of cell phen

221 rovides a set of multivariate non-parametric statistical methods that test a complex null hypothesis

222 valence because we lack generally applicable statistical methods that yield numerical estimates for c

223 Using novel statistical methods, they detected similar deficits acro

224 Using exploratory statistical methods, this study explored the possibility

225 We built upon a statistical method to describe metacommunity structure t

226 euronal assemblies calls for a comprehensive statistical method to describe, analyze and characterize

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

228 The standard statistical method to determine whether a gene is an eGe

229 ute shrinkage and selection operator (Lasso) statistical method to diagnose pancreatic tissue section

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

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

232 e in ARDS by Mendelian randomization (MR), a statistical method to infer causality using observationa

233 We use a state-of-the-art statistical method to quantify a CRM's sequence similari

234 We first applied the same LIMMA statistical method to re-analyze the Gaucher data set an

235 Here we present a novel adaptive statistical method to simultaneously address both proble

236 In this article, we develop a novel statistical method to test associations between a geneti

237 events, leveraging powerful, haplotype-based statistical methods to analyse 1413 individuals from acr

238 challenge, and there are still only very few statistical methods to analyze more than two genomic var

239 cial neural network (ANN) modeling and other statistical methods to analyze relationships between a h

240 zation, but the development of comprehensive statistical methods to analyze screen data has lagged.

241 We provide guidelines for using statistical methods to analyze the types of experiments

242 econdary outcomes in advance, specifying the statistical methods to be applied, and making all data o

243 However, the field currently lacks statistical methods to calculate sample size and estimat

244 There is a need for statistical methods to combine and preprocess segmented

245 The application of statistical methods to comparatively framed questions ab

246 We then assessed statistical methods to detect changes in m(6)A peaks as

247 records to evaluate rates of AKI and various statistical methods to determine their relationship to C

248 or imaging) in combination with multivariate statistical methods to differentiate patients diagnosed

249 The objective of this study was to use statistical methods to disaggregate all publicly funded

250 tions in large cohorts of patients and using statistical methods to discriminate driver from passenge

251 entify periods of vulnerability, we used two statistical methods to estimate phthalate-adiposity asso

252 We extend statistical methods to estimate the frequency, i.e. the

253 We used three statistical methods to examine the shape of the concentr

254 y measure phenotypes, and developed a set of statistical methods to extract genetic interactions from

255 gh representational capacity of multivariate statistical methods to identify neuroimaging-based bioma

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

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

258 e option of selecting from several different statistical methods to perform differential methylation

259 nearly 15 bioinformatic tools and enrichment statistical methods to propose and validate a drug combi

260 oses and traits, and with the application of statistical methods to rare variants, it is important to

261 We applied different model assumptions and statistical methods to real-life outcome data from a wel

262 We have used sophisticated but accessible statistical methods to reveal that spatial components-wh

263 observational analyses, we used traditional statistical methods to test the shape of association bet

264 We employ a statistical method, TROM, to identify both protein-codin

265 ection of bias were complex functions of the statistical method used, mortality rates and distributio

266 So far, the statistical methods used have been rudimentary, employin

267 e relationships affect the results of common statistical methods used in observational studies.

268 By applying the statistical methods used in previous studies [1-4, 6] to

269 er, it remains controversial in part because statistical methods used to analyze readmission, primari

270 bias, primarily due to the sample size, and statistical methods used to develop and select the predi

271 es in clinical study designs and the various statistical methods used to identify associations.

272 Statistical methods used were Cox regression, Student t

273 though there is not yet a consistency in the statistical methods used.

274 -boosted model and compared with traditional statistical methods using 2 independently derived logist

275 A novel adaptation of established statistical methods was then used to test for enrichment

276 TwoPhaseInd implements a number of efficient statistical methods we developed for estimating subgroup

277 As a pre-specified statistical method, we determined differences in total e

278 he recent controversies in some neuroimaging statistical methods, we compare the most frequently used

279 By combining different statistical methods, we could detect, quantify, and expl

280 Using well-established statistical methods, we developed a novel framework for

281 Employing a combination of statistical methods, we selected seven Cys34 adducts ass

282 Applying new statistical methods, we show that the sensitivity, speci

283 Using spatially referenced data and statistical methods, we track from 2000 to 2012 the impa

284 Advanced statistical methods were applied to expose any relevant

285 Reporting quality and statistical methods were assessed using components of th

286 Standard statistical methods were carried out to investigate the

287 Statistical methods were then used to identify proteins

288 r cardiovascular disease, although different statistical methods were used for this analysis.

289 Multivariate statistical methods were used to classify samples and id

290 Statistical methods were used to determine confounders a

291 Complementary univariate and multivariate statistical methods were used to identify biomarkers ass

292 Bayesian statistical methods were used, with the pre-specified me

293 ng equations and Spearman's rank correlation statistical methods were used.

294 Recently, Jiang and Zhan proposed a statistical method which introduces sample-specific norm

295 Here, we present a novel statistical method, which we refer to as scPLS (single c

296 Here, we present a statistical method with statistical guarantees that test

297 ing of archaic admixture in humans relies on statistical methods with large biases, whose magnitudes

298 of the original data using state-of-the-art statistical methods with permutation procedures for test

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

300 basis for subsequent application of rigorous statistical methods, with the ultimate goal being the cl