ライフサイエンスコーパス: validation

1 elopment and a one third set (Nv = 5042) for validation.

2 robust nutritional biomarker development and validation.

3 out during model building and later used for validation.

4 nal DRS performance metrics with the dry-run validation.

5 the most confident variants for experimental validation.

6 s a general framework for preclinical target validation.

7 variables not used directly provide a model validation.

8 ed for calibration and 868 used for external validation.

9 r chemical probes used in preclinical target validation.

10 el oral-specific mock community for pipeline validation.

11 SSIDOR 2 and E-Ophtha databases for external validation.

12 utations from these positions for functional validation.

13 l-modality may therefore be used a means for validation.

14 ng bioinformatics analysis with experimental validation.

15 ble for novel drug target identification and validation.

16 ors are publicly available for discovery and validation.

17 t essential step in structure assignment and validation.

18 elated protein, which was selected for ELISA validation.

19 ered independent experimental comparison and validation.

20 Partners Biobank were genotyped and used for validation.

21 ds as well as the prerequisites for clinical validation.

22 S method which underwent a rigorous in-house validation.

23 was internally validated using 10-fold cross-validation.

24 oposed to prioritize variants for functional validation.

25 collected, and then tested it in an external validation.

26 oil goggles to simulate blur for comparative validation.

27 ated through 1000 iterations of 5-fold cross-validations, 1000 bootstrapping validations and 1000 per

28 se chain reaction in independent samples for validation (40 patients with IS and 40 matched controls)

29 These validations add to the therapeutic value of LumC13 (Lumi

30 Validation against approximately 600 experimental mutati

31 The validation analyses included 189539 participants (mean a

32 In external validation analyses, a genetic score consisting of varia

33 tial confidence to target identification and validation analyses.

34 Validation analysis by qRT-PCR showed significant upregu

35 seful candidates have been identified, their validation and adoption into clinical use remain challen

36 ance immunosuppression management, but await validation and clinical implementation.

37 analytical results were challenged by method validation and comparison with the results of the liquid

38 Through leave-one-out cross validation and cross-classification on independent datas

39 view will provide topical coverage of target validation and drug discovery efforts made in targeting

40 rioritize differentially expressed genes for validation and functional assessment.

41 ng experiments based on both five-fold cross-validation and independent tests indicated that the perf

42 rmance of our method using both 5-fold cross-validation and independent tests.

43 rve) that reaches 0.65 both in 10-fold cross-validation and on an independent test set.

44 multivariate statistics, as well as internal validation and propensity score matching of factors know

45 iations with phenotype paths in HPO in cross-validation and the prediction of the most recent associa

46 odulators of biomolecules without sufficient validation and then propagated in the scientific literat

47 hlighting the importance and power of strain validation and whole genome sequencing in this context.

48 5-fold cross-validations, 1000 bootstrapping validations and 1000 permutation tests (that assessed th

49 rence data is essential for the development, validation, and implementation of in vitro and in silico

50 These differences need validation, and their impacts on disparities need more d

51 gned contig regions (long read support based validation approach).

52 Because diagnostic development and validation are time consuming, they should be carried ou

53 Mean validation areas under the receiver operating characteri

54 Independent validation assays of individual genes confirmed coloniza

55 iables could not achieve any classification (validation AUC: 0.50; 95% CI: 0.36, 0.64).

56 -pyridone-5-carboxamide, that can be used as validation biomarkers for the treatment.

57 llowing lab validation, we performed a human validation by collecting fingerprick whole blood samples

58 on of ICAM-1 protein expression on cells and validation by immunohistochemistry on human tissue speci

59 ody-based immunofluorescence microscopy with validation by mass spectrometry.

60 d, including time for APEX2 fusion construct validation, cell growth, and solidification of embedding

61 statistic 0.84, 95% CI 0.82-0.86) and in the validation cohort (0.79, 0.73-0.84).

62 for the development cohort and 10.9 for the validation cohort (95% CI, 7.54-14.30) (P = .08).

63 These characteristics were confirmed in the validation cohort (c-statistic, 0.828).

64 The validation cohort (n = 759) was taken from a prospective

65 The same was true for the validation cohort (p53: adjusted OR 8.6; 95% CI, 0.93-80

66 015 at hospitals in Belgium and Switzerland (validation cohort 1) and in liver biopsies from 20 patie

67 2012 through May 2015 in the United States (validation cohort 2).

68 In validation cohort 2, the gs-MELD discriminated patients

69 The validation cohort consisted of 122 consecutive patients

70 discovery cohort had 306 patients, the first validation cohort had 216, and the second validation coh

71 st validation cohort had 216, and the second validation cohort had 265 patients.

72 The validation cohort included 18 ACAs and 16 ACCs.

73 s and 25 643 controls from NINDS-SiGN, and a validation cohort of 10 307 ischaemic stroke cases and 2

74 ensitivity in both the original cohort and a validation cohort of 120 different subjects.

75 We studied a validation cohort of 98 heart recipients transplanted in

76 a 2-step manner in a screening cohort and a validation cohort of pre-PML and NTZ-ctr patients.

77 In the validation cohort patients with antibody-mediated condit

78 Model calibration in the validation cohort was excellent, with a slope of 0.97 (s

79 uired pneumonia to 29 ICUs in the UK (second validation cohort).

80 In this validation cohort, plasma derived exosomal miRNA was iso

81 In the validation cohort, prognosis worsened with increasing HA

82 In the recent adult validation cohort, the model retained excellent performa

83 In the validation cohort, the proportion of patients assigned t

84 In the validation cohort, the score had an area under the recei

85 In the validation cohort, the score showed a good prediction of

86 .041) and NOD2 (p = 0.045) in an independent validation cohort.

87 pe was 0.9966 (P = .99), determined from the validation cohort.

88 ts with ATTR V122I amyloidosis comprised the validation cohort.

89 Validation of the CRS was performed in the validation cohort.

90 s maintained excellent discrimination in the validation cohort.

91 immunosuppressive capacity of MSC lines in a validation cohort.

92 accuracy of 97% (95% CI, 89% to 99%) in the validation cohort.

93 tent and reached nominal significance in the validation cohort.

94 groups in both the discovery cohort and the validation cohort.

95 tudy was divided into 2 groups, a test and a validation cohort.

96 sed a training cohort (in Germany) and three validation cohorts (in Germany and the USA) of patients

97 st additions 9 years later in derivation and validation cohorts (R(2) = 0.9).

98 nce was assessed using internal and external validation cohorts and compared to clinical assessment a

99 did unsupervised class discovery of test and validation cohorts to identify consensus primary molecul

100 2011, and July 20, 2012 (discovery and first validation cohorts) and patients admitted with sepsis du

101 e Hosmer-Lemeshow test in the derivation and validation cohorts, and assigned a simplified point-scor

102 istic of 0.76 and 0.75 in the derivation and validation cohorts, respectively.

103 5, 0.91-0.98) and external (0.91, 0.85-0.95) validation cohorts.

104 Moreover, numerical validations confirm an error below 0.02% for events at r

105 In vitro and in vivo validation confirmed that OncoLead analysis can recapitu

106 0.782 versus AUC=0.744, P<0.0001) but not in validation data (AUC=0.749 versus AUC=0.747, P=0.785).

107 classify all samples in the calibration and validation data sets, providing 100% prediction accuracy

108 In validation data, the signature discriminated cases that

109 The validation dataset consisted of 241 patients from an aca

110 rediction experiments were evaluated using a validation dataset, and biological verification was perf

111 Model predictions were compared with the validation dataset, and mean predicted error was calcula

112 SE of 0.86 and 0.94% for the calibration and validation dataset, enabling quantification of the prote

113 ure space was then assessed using a separate validation dataset.

114 predicting disease inheritance modes for all validation datasets.

115 remor and essential tremor, in both test and validation datasets.

116 Rigorous cross-validations demonstrate the superior prediction quality

117 We adopted a two-stage discovery and validation design using patients from the PROFILE cohort

118 the proposed methodology was demonstrated in validation experiments for the recovery and detection of

119 antly reduce the cost and time of subsequent validation experiments.

120 hers as to their function and a framework of validation for future experimental work.

121 Model validation for prediction of overall survival and non-re

122 , 2 and 3 were discovery, prioritization and validation for tracking suicidality, resulting in a Top

123 Validation group patients divided into 10 subgroups by t

124 challenge and duodenal biopsy, but requires validation in a larger study.

125 cordings from 6068 pairs of rat neurons with validation in additional mouse and human neurons and mul

126 Upon validation in additional study sets, the alterations of

127 External validation in Alzheimer's Disease Neuroimaging Initiativ

128 Analyses of the melanoma secretome and validation in clinical specimens showed that the heparin

129 Validation in clinical trials and translation to care wo

130 Further validation in cohorts with severe obesity and engineerin

131 complementary biological reagents for target validation in drug discovery.

132 ent institutions and is now open for further validation in gliomas and other cerebral diseases.

133 operative diagnosis of ACC but needs further validation in larger cohorts of patients.

134 ve pulmonary disease (COPD) require external validation in order to assess their clinical value.

135 Further validation in other countries is needed.

136 l dysfunction in cirrhosis, although further validation in patients with more advanced cirrhosis and

137 utcomes, are in development and will require validation in prospective trials.

138 irway, which needs further investigation and validation in the clinical setting.

139 AM1) were used for optimization, followed by validation in the parent endocrine-dependent cell line (

140 We performed a clinical validation in which we compared measurements from whole-

141 Validation included epigenetic and cellular assays.

142 at the heritability calculated through cross validation is equivalent to trait predictability, which

143 ly on statistical association, so functional validation is necessary to make strong claims about gene

144 f specific organic contaminants, but further validation is needed.

145 During validation limits of detection (LOD) and quantification,

146 The validation method was confirmed by analysis of rice flou

147 ith biochemical fractionation and additional validation methods reported here could be useful to disc

148 g well-characterized controls and a panel of validation methods.

149 omly grouped into derivation (n = 2,247) and validation (n = 1,124) sets.

150 ed in the derivation (n = 33820) or external validation (n = 54716) data sets.

151 ndomly divided into derivation (n = 654) and validation (n = 650) cohorts.

152 ificity for depression subtypes in multisite validation (n = 711) and out-of-sample replication (n =

153 data were divided into training (n=1625) and validation (n=637) set.

154 ent replication in other cohorts, and robust validation of 107 independent loci.

155 We here perform a rigorous validation of 13 anti-ERbeta antibodies, using well-char

156 d resources including the identification and validation of 234,452 putative single nucleotide polymor

157 e present study aimed at the elaboration and validation of a method to determine PAs and TAs in honey

158 Herein, we describe the training and validation of a new assay that measures the proliferatio

159 aims of this study were the optimization and validation of a new ultrasound assisted phytosterol meth

160 ptimization, analytical characterization and validation of a novel ion-selective electrode for the hi

161 We now report the development and technical validation of a rabbit monoclonal antibody-based sandwic

162 Validation of a theoretical model using the experimental

163 Furthermore, the validation of an exosome-associated biomarker in the blo

164 Here, we review the development and validation of assays that directly and indirectly measur

165 After validation of both methods, we evaluated the levels of b

166 Finally, epidemiological validation of candidate biomarkers was performed in two

167 nical decision-making support tools, and the validation of clinically relevant imaging biomarkers.

168 ach for identification, characterization and validation of deleterious non-synonymous SNPs (nsSNPs) i

169 to improve practice, while also allowing for validation of disseminated research.

170 ein, we report the design, optimization, and validation of double-click stapled peptides encoding the

171 ethylomes across multiple tissues will allow validation of epigenome association studies and explorat

172 models currently used in clinical practice; validation of FABP1 as a clinical prediction tool in APA

173 Clinical validation of FGFR as a therapeutic target has been demo

174 ide a bench-to-bedside review on preclinical validation of IDO1 as a cancer therapeutic target and on

175 c architecture, thus enabling the functional validation of known genetic risk factors and potentially

176 mixture, and represents the first mesoscopic validation of leading theories concerning the variation

177 andard reference materials were analyzed for validation of method.

178 However, the personalized identification and validation of neoantigens remains a major challenge.

179 e molecules relies on the identification and validation of new target structures in close conjunction

180 Further validation of NLRP3 priming in vivo involved administrat

181 nd outline strategies for identification and validation of novel putatively pathogenic variation in t

182 Identification and functional validation of oncogenic drivers are essential steps towa

183 First, as a validation of our approach, we demonstrate that a greate

184 g (SRM)-based approach for the discovery and validation of peptide biomarkers for cancer.

185 Validation of probe targets and "G" and "H" site specifi

186 ts were identified by metagenomics, enabling validation of robust in vivo RNA-guided DNA interference

187 he NCT00632476 trial followed by independent validation of selected cord blood differentially methyla

188 lasmon resonance experiments resulted in the validation of seven dose-dependent C3b-binding compounds

189 Experimental validation of several novel microRNAs in C. reinhardtii

190 Validation of simulated tissue outcomes on an independen

191 s an important platform for accelerating the validation of small molecules that target MmpL3, and the

192 egies and minimal consensus criteria for the validation of SUMOylation that can be applied to any SUM

193 Establishment, specification, and validation of synaptic connections are thought to be med

194 The validation of the algorithm yielded an average of 95.8%

195 Firstly, validation of the approach was performed by correlating

196 Validation of the automated monitoring system with the c

197 authors present the development and initial validation of the Carolina Premenstrual Assessment Scori

198 Validation of the cgMLST scheme was undertaken with 1,47

199 sis of the resulting reaction curves enables validation of the critical dPCR assumptions that are ess

200 Validation of the CRS was performed in the validation co

201 riments also allow us to make a quantitative validation of the kinetic modification expected to occur

202 Validation of the model by introduction of data of secre

203 Findings of this study provided validation of the Myotonometry technique and its high se

204 The validation of the new method gave satisfying intra-day a

205 characterized, hindering direct experimental validation of the offline hypothesis and elucidation of

206 Independent validation of the prediction and prognostic performance

207 gene regulatory network (GRN) with in vitro validation of the predictions, we sought to determine th

208 Validation of the results was achieved by preparing spec

209 single-particle cryo-electron microscopy and validation of the structure using footprinting and cross

210 Validation of the system has been carried out using a to

211 , work has focused on the implementation and validation of the thermodynamic poise calculation itself

212 Therefore, discovery and validation of therapeutic targets derived from the hypox

213 As a validation of this approach, we identified a novel Serto

214 The present article describes the validation of this method, which was performed according

215 Validation of this novel predictive score is needed to c

216 Functional validation of this transporter gene revealed that in vit

217 Experimental validation of TPS predictions for barrier crossing estab

218 ubstrates have been proposed over the years, validation of true NEDD8 targets has been challenging, a

219 er was the prototype for the development and validation of what was then a highly innovative method f

220 Validation on tap water samples spiked with different co

221 External model validation on the REACH trial and sensitivity analyses c

222 orted by two parallel routes of experimental validation, our results indicate that natural spinning i

223 The validation panel, sequencing analytics, and raw sequence

224 rical simulations, supported by experimental validation, predict that rare fixers will invade a popul

225 A complete method validation procedure was conducted to evaluate the effec

226 y of the models was confirmed by an external validation procedure with an independent sample set.

227 According to the two-phase selection and validation process, we found that miR-25, miR-29a and mi

228 For validation purposes, recovery studies were carried out a

229 rm for therapeutic target identification and validation, respectively.

230 ons, summarize the large-scale retrospective validation results, and discuss limitations of the metho

231 Validation revealed that miR-181b-5p, miR-21-5p, miR-195

232 In PLS-R the Root Mean Square Error of Cross Validation (RMSECV) for parasite concentration (0-5%) wa

233 Mortality in the derivation and validation sample was 11% and 8% at 28 days and 34% and

234 models were validated in a Monte Carlo cross-validation scheme.

235 Within this validation, senescent cells were recognized with 93% sen

236 was associated with firearm violence in the validation set (odds ratio [OR], 1.47 [95% CI, 1.23 to 1

237 0.5 procedures per patient versus 41% in the validation set after 1.5 +/- 0.5 procedures per patient

238 The validation set comprised 46 subjects (29 with IBS and 17

239 The validation set exhibited similar clusters, demonstrating

240 9 splicing events, which were confirmed in a validation set from The Cancer Genome Atlas.

241 dicted LTx or ITx rejection in corresponding validation set samples in the 60-day postsampling period

242 research-grade reagents and 122 independent validation set samples were tested with current good man

243 re optimized and then further confirmed on a validation set.

244 ctions, we compare accuracies on holdout and validation sets for three privacy-preserving the reusabl

245 Through rational design of training and validation sets, key diastereoselectivity outliers were

246 Independent validation-sets confirmed the genes DLG1, METTL7A, KIAA1

247 Bootstrapping validation showed negligible optimism.

248 Extensive experimental validation showed that AtRTD2 and its modified version,

249 Biological validation showed that PCSK9 promoter methylation is con

250 Rigorous cross-validations showed that the proposed predictor achieved

251 In the validation stage, we confirmed these changes for five ty

252 During the validation step, the following parameters were determine

253 s that survived Bonferroni correction in the validation step.

254 Finally, validation studies in humans demonstrate that the V PC/V

255 Specific validation studies will be necessary to determine the be

256 ver a 1-year period in the women's Lifestyle Validation Study (2010-2012), conducted among subgroups

257 This was followed by a validation study in 30 selected patients with and withou

258 A validation study on 21 breast cancer cell lines showed t

259 f 775 healthy women in the Women's Lifestyle Validation Study that was conducted within the NHS (Nurs

260 consistent performance in the out-of-sample validation study.

261 ive, cross-sectional, comparative instrument validation study.

262 alyses of TCGA and ICGC cancer datasets, and validations, suggest that VALORATE is accurate, fast, an

263 proved our final prediction by using a cross-validation test.

264 ; internal test sets, 66.7%; external (blind validation) test set, 68.4%.

265 "clinicogenetic" risk model development and validation that apply to FL and more generally to other

266 This study provides prospective validation that functional connectivity between an indiv

267 for Mendelian conditions, and repeated cross-validation that optimizes its discriminant power.

268 After internal validation, the AUCs decreased to 0.74 and 0.54, respect

269 After optimizing the feature sets via cross-validation, the trained classifiers enable identificatio

270 Validation through enzyme assays and customized (13) C m

271 r, and human disease traits and experimental validation to demonstrate that genetic variation affects

272 ssessed and validated by using 10-fold cross-validation to limit the effect of optimistic bias.

273 rization, which uses repeated internal cross-validation to select variables and estimate coefficients

274 ry pipeline - from target identification and validation, to target-based and phenotypic screens, to c

275 pared using published criteria, and internal validation using bootstrap methods was performed.

276 lysis of IRE1alpha- and XBP1-depleted cells, validation using RNA cleavage assays, and 5' RACE identi

277 Structure validation was achieved by conversion of cycloadducts in

278 Validation was based on analyses at three fortification

279 Further validation was done using data from a fifth trial-ENTHUS

280 he most robust tryptic peptide marker in the validation was LTLGSALAAPQR.

281 Methodological validation was performed by using cold vapor atomic abso

282 -DA) with double leave-one-patient-out cross-validation was performed to distinguish tumors from beni

283 urve (AUC), predicting 5-year risk; internal validation was performed using 1000 bootstrapped resampl

284 External validation was performed using data from three other hos

285 An independent validation was performed where each independent study wa

286 Ten-fold cross validation was used to evaluate prediction accuracy with

287 As an orthogonal validation, we directly compared tracer distribution pat

288 During 10-fold cross validation, we increased the accuracy of the classic BL

289 Following lab validation, we performed a human validation by collectin

290 silico prediction and subsequent functional validation, we were able to identify a MHCII-restricted

291 lation coefficient analysis, and test-retest validation were conducted.

292 le-genome bisulfite sequencing data sets and validation with 101 reduced-representation bisulfite seq

293 Validation with an external test set suggests that the m

294 s in the mature mouse brain with RNA-Seq and validation with independent methods.

295 ivo comparative studies and, when available, validation with knockout animal models or structurally d

296 We demonstrate platform validation with patch-clamp recordings from a variety of

297 Upon validation with quantitative PCR, we studied the associa

298 The validation with the chromatin immunoprecipitation (ChIP)

299 Although these results are early and need validation with transplantation, this technology has pro

300 language impairment, followed by independent validations with Sanger sequencing, and analyses of segr