ライフサイエンスコーパス: data analysis

1 ructures and classify them using topological data analysis.

2 and informed by extensive population health data analysis.

3 Both trials were completed and closed before data analysis.

4 sed for experimental design and multivariate data analysis.

5 l SERS approach without the need for complex data analysis.

6 with a cutoff date of November 1, 2015, for data analysis.

7 f the demodulation frequency (nomega) during data analysis.

8 contributions to the FSCV data that confound data analysis.

9 d by hierarchical clustering and topological data analysis.

10 n the time and effort required for miRNA-seq data analysis.

11 ntegrated pipeline for Iso-Seq transcriptome data analysis.

12 followed from 33 to 84 months at the time of data analysis.

13 esonance (NMR) spectroscopy and multivariate data analysis.

14 ves the reliability of stable isotope tracer data analysis.

15 , ultracentrifugation, data acquisition, and data analysis.

16 lf has become a workhorse in single molecule data analysis.

17 e), were utilized to expedite pyrosequencing data analysis.

18 with a reliable and robust framework for RNA data analysis.

19 nce the study was an observational secondary data analysis.

20 the standard preprocessing pipeline for MRI data analysis.

21 Both outcomes were determined prior to data analysis.

22 tresses, as indicated by previous microarray data analysis.

23 n online platform for high-throughput screen data analysis.

24 flexible, streamlined and comprehensive CLIP data analysis.

25 Retrospective data analysis.

26 (PiMP) fulfils an unmet need in metabolomics data analysis.

27 -links, independent of the software used for data analysis.

28 in scientific studies to improve comparative data analysis.

29 sing, DNA sequencing, control inclusion, and data analysis.

30 library used for targeted, peptide-centric, data analysis.

31 crease the accuracy and accessibility of GBS data analysis.

32 an intestinal biopsies were used in clinical data analysis.

33 R and Bioconductor were used for data analysis.

34 and a new algorithmic design XlinkX v2.0 for data analysis.

35 imple experimental setup and straightforward data analysis.

36 complexity that is compatible with real-time data analysis.

37 alysis, Cluster Analysis) have been used for data analysis.

38 -automated user-guided error correction, and data analysis.

39 lomics techniques, biospecimen handling, and data analysis; (3) application to studying the role of t

40 In our pooled data analysis, 634 patients were treated for 8 weeks wit

41 codes to study in-hospital events); and (3) data analysis (accounting for complex survey design of t

42 tation of the assay (experimental design and data analysis), affinities of the monosialoganglioside l

43 lex datasets will, with the help of advanced data analysis algorithms, lead to fundamental insights i

44 me databases and user-friendly pipelines for data analysis, all accessible at lower cost.

45 ato Expression Atlas to facilitate effective data analysis, allowing the simultaneous visualization o

46 larized matrix factorization, (2) functional data analysis and (3) canonical correlation analysis (CC

47 vailable air-cooled CCD, a new estimator for data analysis and a high heralding efficiency photon-pai

48 ition, we present an algorithm for automated data analysis and a multiplexing system promoting practi

49 nclusions are strongly supported by rigorous data analysis and by numerical simulations, all in perfe

50 spectrometry data acquisition and 1-2 d for data analysis and downstream informatics.

51 Through a series of data analysis and drug screening, we identified two comp

52 amatically simplifies high-throughput screen data analysis and enables researchers to dig deep into t

53 duces computational challenges for automated data analysis and hinders translation of new biological

54 gh the combination of retrospective clinical data analysis and in vitro imaging in the space between

55 s data necessitates novel methods for deeper data analysis and interpretation.

56 m assay design and reagent identification to data analysis and interpretation.

57 equences, which markedly improve metagenomic data analysis and interpretation.

58 HMM) has been a workhorse of single-molecule data analysis and is now commonly used as a stand-alone

59 s are pledging to make code they produce for data analysis and modeling open source, and are actively

60 n urgent need to define common standards for data analysis and reporting formats of cross-linked prod

61 s samples faces severe challenges concerning data analysis and results interpretation.

62 e-based approaches to vertically distributed data analysis and test their performance using 5 example

63 Here we present CRISPR-DAV (CRISPR Data Analysis and Visualization) pipeline to analyze the

64 in the quality of high-throughput biosorter data analysis and visualization, opening new options for

65 can be estimated at different points during data analysis, and are most relevant for residue or prot

66 line tools, real-time computing, interactive data analysis, and cross-platform analyses feature WebGL

67 The performance was compared to a 'naive' data analysis approach, by using computer simulation, ev

68 gh thoughtful experimental design and robust data analysis approaches.

69 ovements in imaging, sensor technologies and data analysis are now making high-throughput root, shoot

70 Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these hi

71 The data analysis based on the compression tests suggests th

72 ces are typically discounted in modeling and data analysis because their contributions are assumed to

73 Data analysis began on September 1, 2016.

74 ross-linking data sets requires an automated data analysis by dedicated software tools, but applying

75 e entire procedure, from virus production to data analysis, can be completed in approximately 10 d.

76 several experimental design considerations, data analysis challenges, and statistical epidemiologica

77 xtending from March 2011 to April 2015, with data analysis conducted from November 2015 to May 2016.

78 ent eligibility criteria; conducted original data analysis; considered safety concerns, potential ben

79 d is inconclusive but argue that model-based data analysis does offer a way to make progress.

80 Data analysis explored the age of diagnosis, hearing aid

81 v) mass spectrometry (MS) analysis; and (vi) data analysis for identification of glycans using in-hou

82 Data analysis for the current investigation was performe

83 Data analysis for this study in a UK general community w

84 The development of intelligent data analysis from a machine learning perspective provid

85 Secondary data analysis from a prospective study.

86 t-generation sequencing data, with iterative data analysis from targeted, whole-exome, or whole-genom

87 While the focus of connectomic data analysis has been on neurite reconstruction, synaps

88 Still, many questions remain open, and data analysis has to be optimized to avoid interpretatio

89 The real data analysis identified one important gene, angiotensin

90 Lipid identification is based on MS/MS data analysis in accordance with defined fragmentation r

91 tlas are from a new high-depth Structure-seq data analysis in Arabidopsis thaliana, released with thi

92 al discovery to become a part of the routine data analysis in systems biology.

93 e cases that illustrate the value of putting data analysis in the hands of those looking to explore t

94 vant computational toolsets required for the data analysis in their knowledge discovery process.

95 Data analysis included the calculation of within-subject

96 ques in disciplines dealing with big network data analysis including biology, medicine, and social sc

97 Subsequently, an unsupervised multivariate data analysis including principal component analysis (PC

98 2 integrates all steps required for ChIA-PET data analysis, including linker trimming, read alignment

99 However, PELDOR data analysis is more challenging in systems containing

100 health care data and computational tools for data analysis is that the process of data mining can bec

101 machine vision techniques improve, automated data analysis may become an increasingly practical suppl

102 REVIEW Components of meta-study (meta-data-analysis, meta-method, and meta-theory) were employ

103 Here, we present a new data analysis method that combines mechanistic stochasti

104 Current conventional and even advanced data analysis methods for MFC data explore only a subset

105 rbitrary experiments on it to see if popular data analysis methods from neuroscience can elucidate th

106 Here we provide a survey of data analysis methods starting from an overview of basic

107 ars to be suitable for the evaluation of all data analysis methods that utilize the proper experiment

108 esearch, scientists are in need of efficient data analysis methods.

109 growth and sampling methods), and different data analysis methods.

110 east and Ovarian Cancer in Cologne, Germany; data analysis, November 1 through December 31, 2015.

111 Data analysis occurred between January 18, 2016, and Jul

112 Combined experimental data (analysis of guard cell wall epitopes and treatment

113 Methods A secondary data analysis of 512 women cancer survivors (age, 62 +/-

114 tly, validated quantitatively by single-cell data analysis of a synthetic gene circuit integrated in

115 Pooled data analysis of before-after change in active and contr

116 Topological data analysis of clinical and histologic data was perfor

117 To make sequencing data analysis of CRISPR/Cas9 screens more accessible to

118 Pooled data analysis of hotspots by PCR overlapped with hotspot

119 Data analysis of individual lamin filaments resolves a g

120 e-directed mutagenesis, and X-ray structural data analysis of Saccharomyces cerevisiae eEF1A, we iden

121 "flippant" allows for quick, reproducible data analysis of scramblase activity assays and provides

122 Data analysis of the intention-to-treat population was c

123 However, the cost of providing cloud-based data analysis of the mounting datasets remains a concern

124 to this challenge is "TDA," or "topological data analysis," one of the primary aims of which is prov

125 esearch, it is important to revisit existing data analysis paradigms.

126 We present a user-friendly, cloud-based, data analysis pipeline for the deconvolution of pooled s

127 or all data points to be propagated down the data analysis pipeline, weighed with their probability.

128 lt a comprehensive and customizable sRNA-Seq data analysis pipeline-sRNAnalyzer, which enables: (i) c

129 Standard data analysis pipelines for digital PCR estimate the con

130 h tape-lift, Raman mapping, and multivariate data analysis presents a useful tool for forensic invest

131 le, providing a more objective and automated data analysis procedure for absolute dPCR quantification

132 Through our studies, we demonstrate a new data analysis procedure for extracting the dynamic Stoke

133 that have proven useful in each stage of the data analysis process, on the basis of the experience of

134 A computational expert data analysis program, FlavonQ-2.0v, has been developed

135 c oxidase subunit I) and subsequent sequence data analysis provided experimental evidence of low-leve

136 e frequently used in biological studies, NGS data analysis remains a challenging, time-consuming, and

137 records database from the Hong Kong Clinical Data Analysis & Reporting System was used to identify 25

138 Data analysis requires an additional hour.

139 Scientific Data Analysis Resources (SDARs) such as bioinformatics p

140 In data analysis, restriction of the mass range was conside

141 neuroimaging must define best practices for data analysis, results reporting, and algorithm and data

142 Data analysis revealed 1062 differentially expressed gen

143 Integrative data analysis reveals that a total of 37 genes in 24 tra

144 Participants included in the data analysis sample received treatment with escitalopra

145 A uniform data analysis script implementing the protocol was execu

146 We present single-cell topological data analysis (scTDA), an algorithm for topology-based c

147 Importantly, as part of the data analysis, several statistical quality control appro

148 Detailed data analysis showed that the major contribution to the

149 Further data analysis showed that the produced model reassembled

150 Real data analysis showed that three of six analysed tissues

151 emistry (IHC) staining and public microarray data analysis showing that DACH1 was higher in normal br

152 This combination of experimental design and data analysis software allows the identity of a CRM, the

153 ed verbatim and analysed using a qualitative data analysis software package.

154 describe optimized fragmentation schemes and data analysis strategies substantially enhancing the dep

155 data-independent acquisition and a targeted data analysis strategy that aims to maintain the favorab

156 data-independent acquisition and a targeted data analysis strategy that aims to maintain the favorab

157 -unit (GPU)-based processing for interactive data analysis, such as freehand segmentation.

158 Exploratory data analysis suggests stability of wet AMD over the 36-

159 A suitable data analysis system is also required to visualise the r

160 nced mathematical approach named topological data analysis (TDA) to interrogate two perturbed network

161 Topological data analysis (TDA), an unsupervised approach to multiva

162 community engagement, disease surveillance & data analysis, technical quality & capacity building, an

163 , the implementation of modern detection and data analysis techniques has resulted in marked improvem

164 Here we exploit the large-scale data analysis techniques to study the mobile phone calli

165 ally designed to expose graduate students to data analysis techniques, to develop scientific writing

166 we present a Bayesian model for exploratory data analysis that is capable of automatically identifyi

167 an alternative approach based on functional data analysis that may be worthy of exploration.

168 from Biostars, a site focusing on BIOLOGICAL DATA ANALYSIS: The Bio-TDS was compared to five similar

169 nstrated a 10000-fold time savings, reducing data analysis time from days to minutes.

170 n a tail-bud-like geometry with experimental data analysis to assess the importance of ordered and di

171 iled using SPME-GCMS coupled to multivariate data analysis to explore date fruit aroma composition an

172 pectroscopy in combination with multivariate data analysis to quantify changes in secondary structure

173 However, moving personal genome data analysis to the cloud can raise serious privacy con

174 Data analysis took place between February 1, 2016, and D

175 Data analysis took place between January 27, 2004, and D

176 Data analysis took place from April 2016 through July 20

177 Data analysis took place from April 27, 2015, and June 2

178 Data analysis took place from August 1, 2016, to Novembe

179 Data analysis took place from February 4, 2017, to July

180 Data analysis took place from March 12, 2015, to Februar

181 Data analysis took place from May 1, 2016, to June 10, 2

182 Data analysis took place from May 26, 2015, to July 20,

183 We have developed a data analysis tool, DeuteRater, to measure protein turno

184 requently used and accessible mass cytometry data analysis tools, including principal component analy

185 It provides secure on-demand access to data, analysis tools, and computing resources.

186 paration and 6-12 h of run time, followed by data analysis (typically taking 1-3 h).

187 dies highlight the efficiency of exploratory data analysis using computational tools and comparative

188 We apply this to gait data analysis using repeated-measurements data from chil

189 Fast and robust data analysis was achieved by developing computer algori

190 Data analysis was based on individual participant data.

191 Data analysis was conducted between 2014 and 2016.

192 Data analysis was conducted between July 17, 2016, and N

193 Data analysis was conducted between March 1, 2016, to Ap

194 een January 20, 2004, and December 19, 2011; data analysis was conducted between November 12, 2015, a

195 Data analysis was conducted between November 18, 2013, a

196 The data analysis was conducted from 2015 to 2016.

197 Data analysis was conducted from April 15 to December 3,

198 Data analysis was conducted from April 4, 2016, to Septe

199 Data analysis was conducted from August 1, 2016, to May

200 Data analysis was conducted from August 15, 2015, to Aug

201 re network was queried starting in 2009, and data analysis was conducted from December 1, 2014, to Au

202 The data analysis was conducted from December 2014 through J

203 m October 26, 2005, to July 8, 2010, and the data analysis was conducted from December 2014 to Februa

204 The current data analysis was conducted from February 27, 2017, to A

205 Data analysis was conducted from January 1, 2015, to Jul

206 Data analysis was conducted from January 1, 2016, to Feb

207 Data analysis was conducted from January 1, 2016, to Jun

208 The data analysis was conducted from January to December 201

209 ted from July 1, 2008, to June 30, 2015, and data analysis was conducted from July 1, 2015, to August

210 Data analysis was conducted from June 1 to December 15,

211 Data analysis was conducted from June 1 to July 15, 2015

212 Data analysis was conducted from June 1, 2015, to Octobe

213 Data analysis was conducted from March 21 to November 29

214 Data analysis was conducted from March 5, 2014, to Octob

215 The data analysis was conducted from May 2015 to October 201

216 Data analysis was conducted from November 1, 2012, to Ju

217 Data analysis was conducted from November 1, 2015, to Fe

218 Data analysis was conducted from November 1, 2016, to Ap

219 Data analysis was conducted from November 23, 2016, to J

220 Data analysis was conducted from November 25, 2013, to O

221 Data analysis was conducted from October 1, 2016, to Jan

222 Data analysis was conducted from October 1, 2016, to Jan

223 The present study's data analysis was conducted from October 28, 2015, to Au

224 Data analysis was conducted from September 1, 2015, to J

225 Data analysis was done for 137 patients.

226 Data analysis was done from May through July 2015.

227 o a reference regarded as 100% viable cells; data analysis was inspired by that in quantitative polym

228 face of [Formula: see text] The focus of the data analysis was on an 11-residue polypeptide segment i

229 Data analysis was performed between February 1, 2016, an

230 Data analysis was performed between June 2016 and Januar

231 Data analysis was performed from April 1, 2015, to Octob

232 Data analysis was performed from April 21, 2016, to June

233 Data analysis was performed from April 28, 2015, to Febr

234 Data analysis was performed from April 7, 2015, to May 2

235 Data analysis was performed from August 1 through Octobe

236 Data analysis was performed from August 1 to November 30

237 w-up data were used until September 1, 2013; data analysis was performed from August 1, 2013, to June

238 Data analysis was performed from August 1, 2015, to Augu

239 Data analysis was performed from August 27 to September

240 Data analysis was performed from August 8, 2016, to Apri

241 Data analysis was performed from August 9, 2013, to Marc

242 Data analysis was performed from February 23, 2016, to N

243 Data analysis was performed from February 4 to April 14,

244 Data analysis was performed from January 1 to December 3

245 Data analysis was performed from January 1, 1995, throug

246 Data analysis was performed from January 1, 2012, throug

247 Data analysis was performed from January 1, 2015, to Apr

248 Data analysis was performed from January 12, 2016, to Ma

249 Data analysis was performed from January 18, 2016, to Ma

250 was conducted from May 2011 to October 2013; data analysis was performed from January 2014 to October

251 The data analysis was performed from January 5, 2014, to Mar

252 Data analysis was performed from January to July 2016.

253 Data analysis was performed from July 1, 2014, to August

254 Data analysis was performed from July 1, 2014, to June 3

255 Data analysis was performed from July 10, 2014, to March

256 Data analysis was performed from July to October 2015.

257 Data analysis was performed from June 1, 2015, to Decemb

258 Data analysis was performed from June 1, 2016, to Septem

259 Data analysis was performed from June 12, 2015, to May 2

260 Data analysis was performed from June 30, 2013, to Octob

261 Data analysis was performed from June 7 to August 21, 20

262 Data analysis was performed from March 15, 2015, through

263 Data analysis was performed from March 15, 2015, to Augu

264 Data analysis was performed from May 1, 2014, to Decembe

265 Data analysis was performed from May 1, 2016, to July 1,

266 Data analysis was performed from May 7 through October 8

267 Data analysis was performed from November 1, 2015, to Ju

268 Data analysis was performed from November 1, 2016, to Ja

269 Data analysis was performed from November 11, 2015, to F

270 Data analysis was performed from November 15, 2013, to A

271 m December 11, 2012, to October 2, 2015, and data analysis was performed from November 15, 2015, to M

272 Data analysis was performed from November 24, 2015, to N

273 Data analysis was performed from November 30, 2014, to M

274 Data analysis was performed from October 1, 2015, to Jun

275 Data analysis was performed from October 1, 2016, to Feb

276 from October 18, 2011 to December 30, 2013; data analysis was performed from October 18, 2011 to May

277 Data analysis was performed from October 7, 2013, to Mar

278 Data analysis was performed from September 2 to October

279 Data analysis was performed from September 2015 through

280 Data analysis was performed in December 2014 and June 20

281 uclear Medicine, a retrospective multicenter data analysis was started in 2015 to evaluate efficacy a

282 Compositional data analysis was used to describe the distribution of a

283 ling, statistical simulation and large-scale data analysis we study the properties of linear regulato

284 For data analysis, we considered mean choroidal thickness as

285 estimating equations (GEEs) for longitudinal data analysis, we focus on the concordant components and

286 Based on gene expression data analysis, we found that MSI2 expression was highly

287 After data analysis, we have prioritized the chemical series o

288 edure and maintain its high power in genomic data analysis, we propose a new multiple testing procedu

289 The study and data analysis were conducted from April 1, 2010, to Sept

290 apsules, and interventions, assessments, and data analysis were done masked.

291 with complete medical records available for data analysis were included (n = 165).

292 ntial framework for GSEA based on functional data analysis, which utilizes the temporal information b

293 Our methodology for Iso-Seq data analysis will be a useful reference for the study o

294 IP experiment and the subsequent streamlined data analysis with an R package, 'hiclipr'.

295 We find that data analysis with both models without consideration of

296 Data analysis with BP-R(2), a measure that quantifies co

297 ase severity index generated by multivariate data analysis with numerous structural MRI measures as i

298 hese methods can be integrated with existing data analysis workflows by providing initial preprocessi

299 Data analysis workflows typically don't access the full

300 Data analysis yields catalytic exchange rates (at the fo