ライフサイエンスコーパス: data analyses

1 ignment is the first step in most sequencing data analyses.

2 analysis of genome synteny and other genomic data analyses.

3 ieved by means of NMR and mass spectroscopic data analyses.

4 ds for trial selection, data extraction, and data analyses.

5 re confirmed by exhaustive NMR spectroscopic data analyses.

6 rackway and render it useable for subsequent data analyses.

7 variates, we included 61,447 participants in data analyses.

8 rtant pre-processing step for many scRNA-Seq data analyses.

9 he same scripting languages used for primary data analyses.

10 ew and synthesis of methods for claims-based data analyses.

11 l genomic analysis by tighter integration of data analyses.

12 for smoking status and study site in pooled-data analyses.

13 , via a simulation study and 2 epidemiologic data analyses.

14 library preparation, sequencing and RNA-seq data analyses.

15 tware and database systems for cross-species data analyses.

16 Mendelian randomization, and transcriptomic data analyses.

17 ethods are needed to structure the resulting data analyses.

18 d together, which can be important for large data analyses.

19 ormation from PED can be used to boost ChIPx data analyses.

20 ncluded literature reviews and extensive new data analyses.

21 easier and created new tools for preliminary data analyses.

22 erent indicators, detector technologies, and data analyses.

23 ied design,and sampling weights were used in data analyses.

24 lication in different areas of mass spectral data analyses.

25 d logistic regression analysis were used for data analyses.

26 not complete follow-up and were excluded for data analyses.

27 data are a prevailing problem in any type of data analyses.

28 A similar model is envisaged for other NGS data analyses.

29 prospective cohort studies, and multicenter data analyses.

30 fully complete questionnaires were used for data analyses.

31 a concise and retrievable format for future data analyses.

32 e sequence-based PCR (rep-PCR) and web-based data analyses.

33 informatics tools for efficient and accurate data analyses.

34 orted nulls were detected and handled in the data analyses.

35 ptible-infective model motivated by previous data analyses.

36 ion of the lossy compression for statistical data analyses.

37 TWAS approaches in both simulation and real data analyses.

38 nal logistic regression models were used for data analyses.

39 cal flexibility and the statistical power of data analyses.

40 ohorts with and without IBD were included in data analyses.

41 tremely unbalanced or not scalable for large data analyses.

42 hers to relax these two assumptions in their data analyses.

43 ing was based on univariate and multivariate data analyses.

44 a fundamental challenge for various types of data analyses.

45 a latent class logit model was used for the data analyses.

46 rs via extensive simulation studies and real data analyses.

47 al Abstract Reporting System for readmission data analyses.

48 e to rely on different tools to perform such data analyses.

49 that hamper proper functional and structural data analyses.

50 had useable data, and were included in most data analyses.

51 esults and gain more insights into miRNA-seq data analyses.

52 d, however, and could potentially affect CLK data analyses.

53 or routine use in single-cell RNA sequencing data analyses.

54 abolome (UPLC-MS, colonic contents and serum data) analyses.

55 nsidered in multiple regression analyses for data analyses (alpha = 5%).

56 ding design; data collection and monitoring; data analyses and archival; and publication of study res

57 After using topological data analyses and comparing their morphology, number, an

58 In this report we have used a combination of data analyses and computational modelling to investigate

59 Both instrumental data analyses and coupled ocean-atmosphere models indica

60 s that empower users to implement customized data analyses and data views for their particular applic

61 ses laborious, improved tools are needed for data analyses and extraction of key information.

62 lso how they shed light on the complexity of data analyses and interpretation.

63 MR acquisition details, and (iv) the ensuing data analyses and means to precisely calculate the conte

64 We used data analyses and numerical experiments to test this hyp

65 GUI that was designed to support statistical data analyses and prediction for medical and pharmaceuti

66 ng, case ascertainment, case definition, and data analyses and presentation.

67 rs to apply visualizations to understand how data analyses and queries relate to each other.

68 The statistical engine performs several data analyses and statistical summaries.

69 All data, analyses and results are available for download an

70 rigorous data collection, more sophisticated data analyses, and better assessment of management and t

71 at are confirmed in meta-analysis and pooled data analyses, and justifies the imminent launch of the

72 e of PBSCT with BM transplantation, registry data analyses, and the role of the National Marrow Donor

73 orithms, originally developed for microarray data analyses, appropriate for LC-MS data analysis.

74 Implications of these results for data analyses are also examined, and practical guidance

75 y open-source tools for microRNA (miRNA)-seq data analyses are available, challenges remain in accura

76 Currently, most of the scRNA-seq data analyses are commenced with unsupervised clustering

77 e effects of imperfect tests in longitudinal data analyses are not as straightforward to anticipate,

78 ions of biological mass spectrometry, custom data analyses are often needed to fully interpret the re

79 Examples of data analyses are presented, in which ions that may dist

80 Based on the experimental and bioinformatic data analyses as well as mathematical modeling, we deriv

81 general guidance on the reporting of claims data analyses, as outlined in this article, is important

82 boratory procedure and of the flow cytometry data analyses, as well as clinical validation of BAT as

83 Data analyses based on a set of 21 putatively neutral nu

84 lement activities, and facilitating regulome data analyses by serving as pseudo-replicates.

85 Pooled data analyses can increase the potential of addressing i

86 tes the scientific leverage that large-scale data analyses can provide in guiding researchers in an a

87 ing Group study validates that collaborative data analyses can readily be used across brain phenotype

88 e the extent to which global fisheries trade data analyses can support effective seafood traceability

89 is that relationships apparent in aggregated data analyses cannot be assumed to operate at the indivi

90 Powder X-ray diffraction (PXRD) data analyses, computational modeling, and Pawley refine

91 Here we highlight theory and data analyses concerning limitations on the action of na

92 Big data analyses could benefit the planet if tightly couple

93 , whereas the time spent on instrumental and data analyses could vary from 1 to 5 d for different sam

94 date of follow-up was June 29, 2017, and the data analyses cut-off date was June 30, 2017.

95 Overall, both simulation and real data analyses demonstrate favorable performance over exi

96 Simulation and real data analyses demonstrate that our method is accurate, p

97 Simulations and real data analyses demonstrate that SDA outperforms existing

98 Both simulation and real data analyses demonstrate that SPACE is an efficient and

99 Real data analyses demonstrate that the proposed method provi

100 Simulations and real data analyses demonstrate that the proposed method provi

101 Extensive simulation studies and real data analyses demonstrate that the proposed methods prov

102 Simulation studies and real data analyses demonstrate that XP-BLUP adaptively utiliz

103 The resulting protein atlas and our initial data analyses demonstrate the value of proteomics for un

104 Data analyses demonstrated that CaMK2 inhibition changed

105 Data analyses demonstrated that EGM-2 treated PDLSCs pre

106 Both simulation studies and real-data analyses demonstrated that our proposed method was

107 ics, protein quantification, and exploratory data analyses driven by the user via customized workflow

108 f iodine supplementation, along with related data, analyses, evaluations, methods development, and su

109 Traditional HRF data analyses focus on comparing the difference in the m

110 GWASpro was developed to provide data analyses for large-scale molecular genetic data, co

111 In contrast, data analyses for mammalian cardiac injury models indica

112 d statistical approaches that simplifies the data analyses for potential users.

113 eptember 1, 2010, and November 30, 2012, and data analyses for the present study occurred between Jan

114 most common routines in single cell RNA-seq data analyses, for which a number of specialized methods

115 Individual participant data analyses found no significant interaction effects,

116 Here, we report genome-wide data analyses from 110 ancient Near Eastern individuals

117 The lack of longitudinal data analyses from birth to adulthood is hampering long-

118 After the meeting, additional data analyses from large studies were provided to the co

119 Data analyses further demonstrated that force per unit o

120 Crystallographic and docking data analyses have been undertaken using inhibitor compl

121 Recent big data analyses have illuminated marine microbial diversit

122 Recently, however, data analyses have revealed potential pitfalls related t

123 Meta-analyses or pooled data analyses have supported association between ADHD an

124 Multivariate and univariate data analyses highlighted the differences among the samp

125 Integrated RNA-seq and ATAC-seq data analyses identified a subset of differentially expr

126 Data analyses ignored subsequent treatment changes.

127 processing pipelines that could also improve data analyses in animals by using species-specific templ

128 mission tomography (PET) data at the time of data analyses in November 2012 were studied.

129 ntention-to-treat principle and longitudinal data analyses in the context of long-term follow-up.

130 The authors conducted secondary data analyses in three nationally representative househo

131 rrences to use of sophisticated quantitative data analyses in ways that provoke new insights.

132 Secondary data analyses included 1877 STAR*D participants who comp

133 All selection protocols and data analyses included body mass as a covariate, so effe

134 Data analyses included checks on the internal coherence

135 Data analyses included descriptive statistics and multiv

136 Data analyses included receiver operating characteristic

137 extensive simulation study and multiple real data analyses including analysis of real data on gene ex

138 d count data, is crucial for many downstream data analyses including the inference of gene regulatory

139 ariables, and modern multivariate methods of data analyses, including correction of observed associat

140 f-art methods in multiple types of scRNA-Seq data analyses, including data recovery, differential exp

141 rature review; 2) retrospective quantitative data analyses, including linear regression multivariable

142 lysis of samples, we performed multivariable data analyses, including principal component analysis (P

143 aman spectroscopy combined with multivariate data analyses, including principal components analysis a

144 IVPT data were then used with the models in data analyses, including the estimation of prediction in

145 is designed to meet all basic needs of ChIP data analyses, including visualization, data normalizati

146 methods for next-generation sequencing (NGS) data analyses incorporate information regarding allele f

147 Further, both simulation studies and real data analyses indicate that MultiGeMS is robust to low-q

148 These RNA-Seq data analyses indicate that peripheral nerve injury may

149 Model-mediated data analyses indicate that, relative to copper salts, C

150 VOI-based data analyses indicated robust results for scan duration

151 Functional MRI and functional connectivity data analyses indicated that higher-level brain systems

152 Further data analyses indicated that the dye in the marinopyrrol

153 Survival data analyses is performed to compare different prognost

154 As such data sets can be large and data analyses laborious, improved tools are needed for d

155 esonance (NMR) spectroscopy and multivariate data analyses methods are applied to the metabolic profi

156 post roasting as revealed using multivariate data analyses (MVA).

157 post roasting as revealed using multivariate data analyses (MVA).

158 nical classification system, and defined new data analyses needed to refine a classification system.

159 zing the complexity of random assignment and data analyses of a platform trial.

160 eline that automates the quality control and data analyses of ChIP-seq and DNase-seq data.

161 We did longitudinal data analyses of cohorts from the Netherlands (Pediatric

162 These data are consistent with secondary data analyses of large cardiovascular trials and well ad

163 al computational pipeline to readily perform data analyses of protein-protein interaction networks by

164 The authors conducted secondary data analyses of the National Vietnam Veterans Readjustm

165 RNA-seq and microarray data analyses of the putative GLCAT genes revealed gene

166 Full-data analyses of the raw plot-scale data using multileve

167 The data analyses of the studied mixtures reveal that the LN

168 The joint NMR/SANS data analyses of three disease variants (L110V, R153Q, a

169 We performed secondary data analyses of Veterans Affairs intensive care unit (I

170 t screening study of community volunteers to data, analyses of Medicare claims, and recently publishe

171 ial communities are available, metaproteomic data analyses often employ a metagenome-guided approach,

172 Case-cohort data analyses often ignore valuable information on cohor

173 We performed data analyses on 56 samples for which all information wa

174 cts the top significant genes for downstream data analyses or experiments.

175 on clinical impressions rather than rigorous data analyses or expert consensus and none has been full

176 In real data analyses, our model identifies more known and predi

177 Through both simulation and real-data analyses, our studies demonstrated that the propose

178 and computational environments that focus on data analyses over various subsets of a given dataset.

179 Multivariate data analyses (PCA and OPLS-DA) of liver chloroform phas

180 the molecular level, RNA-seq and Methyl-seq data analyses performed in gastrula embryos and metamorp

181 f existing genome browsers with experimental data analyses performed in R.

182 C3NA offers a new microbial data analyses pipeline for refined and enriched taxa-tax

183 Corresponding data analyses provide gene-specific information, and the

184 combined with the findings of the satellite data analyses, provide strong evidence that cholera epid

185 signed to meet the increasing demand for big-data analyses, ranging from bulk sequence processing to

186 Initial data analyses relied on descriptive statistics and strat

187 Additional data analyses requested by the reviewers were conducted

188 DIA data is therefore challenging; most DIA data analyses require spectral libraries.

189 Consequently, data analyses require the computation and storage of mul

190 r of the sieve used, were considered for the data analyses, resulting in a median particle size of 0.

191 Illustrative data analyses reveal encouraging result of this method i

192 Big data analyses reveal that the set of optimal influencers

193 Multivariate data analyses revealed that 2,3-butanediol, hexanal, hex

194 Data analyses revealed that diabetes promoted a proinfla

195 Detailed data analyses revealed that the major advantage of SSIPe

196 Data analyses revealed that the transmembrane portion of

197 TCGA molecular data analyses revealed that VSVZ contact by GBM was inde

198 embryos combined with cell and tissue scale data analyses revealed the asynchronous ingression of ep

199 As shown in simulations and real data analyses, scBatch outperforms benchmark batch-effec

200 In general, reports of claims data analyses should include clear descriptions of the f

201 Detailed data analyses show that the major advantage of IonCom li

202 Detailed data analyses show that the major advantage of MAGELLAN

203 Detailed data analyses show that the major advantage of ResPRE li

204 Data analyses show uniquely different (p < 0.05) charact

205 Statistical data analyses showed that the latter two groups were ser

206 Exploratory classical and compositional data analyses showed that the main changes were due to f

207 Kinetic data analyses showed that the nanofilm responds to TNV w

208 Data analyses started on January 31 and finished June 30

209 mate of relatedness is important for genetic data analyses, such as heritability estimation and assoc

210 ingle-cell RNA-seq and multiome (RNA + ATAC) data analyses, such as uncovering differential gene co-e

211 Real data analyses suggest that CONCUR is well powered to det

212 Both real and synthetic data analyses suggest that our methods can be used to id

213 Modeling and additional data analyses suggest that the balance between the coher

214 Detail data analyses suggest that the major advantage of SED li

215 Results of registry data analyses suggest that the risk of acute rejection d

216 These data analyses suggest the existence of calcium-independe

217 Field data analyses suggested that organic molecules may regul

218 We also observed from our data analyses that for datasets with large sample size,

219 ever, to achieve such a benefit will require data analyses that fully exploit ordinal or continuous-s

220 hanistic hypotheses and a testing ground for data analyses that link neural computation to behavior.

221 strate via simulation study and several real data analyses that our proposed method can perform as we

222 the development of powerful, general-purpose data analyses that process large datasets.

223 We demonstrate with simulations and data analyses that the proposed method not only selects

224 In both data analyses, the possible systematic errors due to non

225 With large scale simulation data and real data analyses, the proposed tests appropriately controll

226 For many observational data analyses, the variability in the treatment selectio

227 The tools perform proteomics data analyses; the libraries enable rapid tool creation

228 and clustering are available for single-cell data analyses, these methods often fail to simultaneousl

229 eview, 3) exploring opportunities for pooled data analyses to answer pressing research questions, and

230 gth of trials, salient outcome measures, and data analyses to be used (especially in the treatment of

231 , high-throughput sequencing and statistical data analyses to enable parallel measurements of the act

232 sion, functional annotation, and exploratory data analyses to highlight subtle expression differences

233 he time course of clinical trials and extend data analyses to include sympathetic as well as sensory

234 ting-edge methods, and timely replication of data analyses to increase the robustness of the findings

235 reduces barriers associated with large-scale data analyses, ultimately facilitating deeper insights i

236 Data analyses used Cohen's kappa statistic, regression m

237 All data analyses used SPSS version 26 and SPSS Modeler 10.

238 ay literature; 2) retrospective quantitative data analyses using Demographic and Health Surveys from

239 Recently, microarray data analyses using functional pathway information, e.g.

240 We present three illustrative data analyses using surrogate variable analysis (SVA) an

241 Our comparative data analyses using three datasets from mouse, human and

242 Data analyses using various bioinformatics tools rely on

243 Furthermore, data analyses--using discriminant analysis of principal

244 d visualization tool EagleView to facilitate data analyses, visual validation, and hypothesis generat

245 Data analyses was performed using Fisher Exact tests ass

246 Using 2-stage individual participant data analyses, we compared 2 common methods of standardi

247 to the database and subsequent comprehensive data analyses, we demonstrate its utility in improving t

248 Through comprehensive simulations and real data analyses, we demonstrate that NITUMID not only can

249 In secondary data analyses, we examined effects of supplementation wi

250 In pooled data analyses, we found significant interaction between

251 reviously published data as well as original data analyses, we show that a sampling-based probabilist

252 By systematic data analyses, we show that the phenomenon stems from th

253 tatory postsynaptic currents with non-biased data analyses, we uncovered a wide range of decay consta

254 Conventional multivariate and compositional data analyses were applied tentatively to investigate th

255 and personnel involved in study conduct and data analyses were blinded to treatment allocation.

256 n October 2, 2017, and October 30, 2019, and data analyses were completed in spring 2023.

257 All data analyses were completed prior to unblinding of the

258 All data analyses were conducted between December 2022 and A

259 Data analyses were conducted between March 1, 2013, and

260 ber 1, 2011, through September 30, 2013, and data analyses were conducted between May 28, 2014, and M

261 All data analyses were conducted from August 2024 to April 2

262 Final data analyses were conducted from February 16, 2015, thr

263 Based on intent-to-treat principle, data analyses were conducted from February 8, 2019, to M

264 Data analyses were conducted from November 6, 2015, to J

265 All data analyses were conducted from September 1, 2022, to

266 n July 21, 1995, and September 11, 1997, and data analyses were conducted in 1999-2001.

267 Data analyses were conducted in QIIME and Phyloseq in R.

268 Data analyses were conducted using generalized estimatin

269 Data analyses were done according to intention-to-treat

270 Data analyses were done from March to September 2016.

271 Data analyses were done on an intention-to-treat basis,

272 Data analyses were done on an intention-to-treat basis.

273 Data analyses were finalized June 24, 2015.

274 Data analyses were initially completed in February 2017

275 ven years but to ensure sufficient power the data analyses were limited to three years.

276 atients, investigators, and those completing data analyses were masked to treatment allocation.

277 een January 1, 2015, and August 5, 2016, and data analyses were performed according to the intention-

278 Study procedures and data analyses were performed at Case Western Reserve Uni

279 Data analyses were performed between December 2015 and J

280 Data analyses were performed between March and November

281 The kinetic data analyses were performed for three different adenovi

282 Data analyses were performed from April 1, 2012, through

283 Data analyses were performed from July 1, 2014, to Decem

284 Data analyses were performed from May 1 through July 1,

285 Data analyses were performed using a computational model

286 Multivariate data analyses were performed using Cox regression.

287 Data analyses were performed using linear random-interce

288 All data analyses were performed using SPSS version 22 and S

289 Untargeted data analyses were performed using the comprehensive mea

290 Descriptive and comparative data analyses were performed.

291 sum, analysis of covariance, and permutation data analyses were performed.

292 Exploratory and multivariable data analyses were used, including logistic regression m

293 formed from the literature and with original data analyses when required.

294 tical role in handling ultrahigh dimensional data analyses when the number of features exponentially

295 olymorphisms, facilitating the use of pooled data analyses which may increase power to detect moderat

296 trials but must often rely on observational data analyses, which are less straightforward and more i

297 s in our cohort attained menarche before the data analyses with a mean +/- SD age at menarche of 11.9

298 e results will provide guidelines to improve data analyses with biochemical networks and facilitate t

299 Here, we combined empirical data analyses with mechanistic model simulations to i) q

300 imulations; additionally, we perform several data analyses with publicly available data and introduce