ライフサイエンスコーパス: analytic

1 orage, with the potential for real-time data analytics.

2 POP), alanine shave mutagenesis, and binding analytics.

3 urface pores by using the HIM and image data analytics.

4 biology to use in machine learning and data analytics.

5 of applications ranging from therapeutics to analytics.

6 he ToF-SIMS data, based on the advanced data analytics.

7 e HP-EMF are compared with predictions by an analytic, a semi-empirical and a numerical model.

8 has been slow to embrace advanced financial analytics, a fundamental message of this review is that

9 Analytic advances are enabling more precise definitions

10 Importantly, the analytic and clinical validity of this assay defines it

11 The development of real-time whole blood analytic and diagnostic tools to detect abnormalities at

12 but more importantly, the integration of new analytic and functional data to improve the quality and

13 TCPA provides various analytic and visualization modules to help cancer resear

14 l version of the GWCoGAPS algorithm contains analytic and visualization tools including patternMatche

15 We identified CPMs in the Tufts Predictive Analytics and Comparative Effectiveness CPM Registry, a

16 s a starting point for further steps of data analytics and modeling of biological dynamics.

17 l core sensing system (CSS) with statistical analytics and modeling to characterize soil at fine dept

18 , which was originally developed for website analytics and social sciences, provides an appealing sol

19 The validation panel, sequencing analytics, and raw sequences could facilitate multilabor

20 permutation (Lasso-Ayers, Lasso-PL) and one analytic approach (Lasso-AL) to select the penalty param

21 We also used a novel analytic approach (Lempel-Ziv complexity) and showed tha

22 We developed an analytic approach and standardised, comprehensive format

23 This analytic approach can discover functional 3D hotspots an

24 epression Rating Scale (MADRS), and the main analytic approach consisted of a linear mixed-model anal

25 Our analytic approach focused on a mother-child dyad case-co

26 REVIEW We used a two-tiered analytic approach including both completed studies with

27 Mendelian randomization refers to an analytic approach to assess the causality of an observed

28 Here, we use a meta-analytic approach to document that coral larval swimming

29 ates the use of a combined genomics and data analytic approach to enhance our understanding of bacter

30 of confounder associations when choosing an analytic approach to estimate sex-specific effects of en

31 n, we used a gambling task and a model-based analytic approach to measure two types of individual sen

32 A mixed model analytic approach was used to evaluate differences in th

33 time were examined, and a sophisticated fMRI analytic approach was used to quantify precisely trialwi

34 Using a 2-level meta-meta-analytic approach with a random effects model to allow f

35 This commentary explains why the meta-analytic approach, frequently used by other attractivene

36 Regardless of the analytic approach, no association was found between the

37 neous, and estimates varied depending on the analytic approach.

38 ere classified using a 'cluster-of-clusters' analytic approach.

39 Lastly, most single-cell RNA-sequencing analytic approaches are not designed to investigate smal

40 Analytic approaches confined to fold-change comparisons

41 INTERPRETATION: Several analytic approaches demonstrated that pirfenidone therap

42 Several analytic approaches demonstrated that pirfenidone therap

43 using any of several advanced computational analytic approaches enables combined anatomic and hemody

44 In this article, we proposed two meta-analytic approaches for LA analysis (MetaLA and MetaMLA)

45 Analytic approaches have included expert review of case-

46 This suggests current analytic approaches in neuroscience may fall short of pr

47 Analytic approaches included linear mixed models based o

48 Analytic approaches initially focused on 475 known or ca

49 Here, we apply the same analytic approaches to a pathological case-control serie

50 First, an overview is given of the current analytic approaches to metabolic brain imaging data.

51 lop a computational platform that integrates analytic approaches to quantify the mechanical output of

52 d to standardize the BRINDA database and the analytic approaches used to address the project's resear

53 of sustained treatment strategies, organizes analytic approaches, provides a structured process for t

54 storage were assessed by using 3 independent analytic approaches.

55 but their unique design may require specific analytic approaches.

56 coherent way, and offers interactive visual analytics approaches to assist the exploration.

57 Using analytic approximations and Monte-Carlo simulations, we

58 ted by the use of data from books and simple analytics based essentially on word counts.

59 The development of a data-driven analytics-based model may assist transplant practitioner

60 A data-driven analytics-based model was developed to predict whether a

61 and catalysis, extraction, electrochemistry, analytics, biotechnology, etc.

62 We derive analytic broadband pi/2 and pi pulses that perform exact

63 However, constructing exact and analytic broadband pulses remains unsolved due to the no

64 We use analytic calculations and micromagnetic simulations to v

65 Hence the scope of high-precision analytics can be extended towards resolving sub-molecula

66 This microassay greatly improves the analytic capacity and efficacy of the method.

67 We describe the major analytic challenges in determining pneumonia etiology an

68 several spatial scales on the basis of meta-analytic coactivation, revealing three broad functional

69 o nine weeks, and analysed them with a micro-analytic coding scheme.

70 Patients and Methods The analytic cohort (n = 220) included patients who had both

71 The analytic cohort included 2488 black and white older adul

72 lated costs and outcomes by using a decision analytic cohort model.

73 The analytic cohort was restricted to 4929 patients with dat

74 (950 TAVR, 883 SAVR) who formed the primary analytic cohort.

75 h of filtered BOLD fMRI time-series, and two analytic components of this oscillatory activity (amplit

76 Both numerical results and analytic considerations indicate that if the components

77 A decision analytic cost-effectiveness model was used.

78 erforming a gain/loss framing task with meta-analytic data from >8000 neuroimaging studies.

79 A richer set of analytic data is also presented, including better tRNA f

80 We then present meta-analytic data revealing distinct subregions within the v

81 Here we applied a meta-analytic data-driven approach to nearly 10,000 fMRI stud

82 Here, we used novel meta-analytic data-driven approaches to characterize the func

83 A, D, and F), as shown in both clinical and analytic data.

84 Through these observations as well as meta-analytic database analyses, we developed a paracrine cro

85 is captured in the MarketScan (Truven Health Analytics) databases.

86 electrochemical and paper-based colorimetric analytic detection platforms is presented as complementa

87 drug conjugate synthesis, drug delivery and analytic detection.

88 Meta-analytic disorder-specific and shared abnormalities in G

89 ndividual countries within each age-specific analytic division, we multiplied randomly selected mean

90 ithout data, we divided countries into three analytic divisions for three age groups (<65 years, 65-7

91 We derive analytic equations and also develop a computational mode

92 This study provides meta-analytic evidence for a significant association between

93 No meta-analytic evidence for interaction between MDD-PRS and CT

94 nuous and completely automated process trace analytics exemplified for the analysis of a CO2 stream i

95 ystems composed of many particles we find an analytic expression connecting the overall velocity vari

96 We derive an analytic expression for the distribution of velocities o

97 We derive analytic expressions for a model's likelihood which is t

98 Compact analytic expressions for force-dependent rates and ruptu

99 n criteria were identified from the Medicaid Analytic Extract database, which includes claims data fo

100 F), or pneumonia using the Medicare Standard Analytic Files and Enrollment Database together with VA

101 set of critical nodes for control, to derive analytic formulas and articulate efficient algorithms to

102 g fMRI studies and laying the conceptual and analytic foundations for future techniques that could ex

103 etation via multikernel learning (SIMLR), an analytic framework and software which learns a similarit

104 (MEGS), we developed a powerful and flexible analytic framework based on a likelihood ratio test and

105 In this paper, we propose a meta-analytic framework for detecting differentially co-expre

106 First, an analytic framework is developed to identify markers of a

107 RNA-sequencing methodology, we introduce an analytic framework that models transcriptome dynamics th

108 acy and biomarker selection for the new meta-analytic framework.

109 d better information compared to traditional analytic frameworks.

110 esponse relationship is demonstrated, and an analytic function describing the time course of the in v

111 nant function analysis to determine the best analytic function to separate healthy and diseased group

112 lustered together on the basis of their meta-analytic functional connectivity.

113 vast datasets and provide interactive visual analytics functions can help scientists achieve deeper i

114 Data were processed through an analytic in-house pipeline.

115 The emerging field of 'predictive analytics in mental health' has recently generated treme

116 functional studies and applied network-based analytics in the search for shared molecular circuits.

117 Integrating analytics in-line enables obtaining a large amount of in

118 This approach provides analytic insights to the formation mechanisms of these s

119 ed via molecular dynamics simulations and an analytic jump model, which provide valuable new molecula

120 with schizophrenia based on the current meta-analytic literature.

121 dministrative claims data from Truven Health Analytics MarketScan Research Databases from 2008 throug

122 Using commercial claims data (Truven Health Analytics MarketScan), we performed a retrospective coho

123 We developed a decision-analytic Markov model to evaluate the cost effectiveness

124 A decision-analytic Markov model was constructed to evaluate the co

125 A decision-analytic Markov model was constructed to evaluate the co

126 Materials and Methods A decision-analytic Markov model was developed for patients with in

127 We constructed decision-analytic Markov models of the natural disease progressio

128 , removal of residual reactants, biochemical analytics, medical diagnostics, therapeutics, and nano-b

129 Our analytic method provides the only feasible means to moni

130 of this article is the development of a semi-analytic method to analyze transport of cargo by multipl

131 intervention type, suicide outcomes, primary analytic method used for linkage, statistical approach,

132 th currently used cumulative incidence based analytic methodologies, and will assist clinical researc

133 However, no classical analytic methods can account for measurement error (ie,

134 report the development of fSTREAM, a set of analytic methods designed to streamline the analysis of

135 is likely overestimated because traditional analytic methods do not separate alpha-retinol derivativ

136 We develop graphical and analytic methods for assessing these scenarios and show

137 nherent low statistical power of traditional analytic methods for discovering G x E.

138 Ever-improving analytic methods for retrieval of empirical data from ar

139 Various testing paradigms and analytic methods have been developed to simplify the dia

140 ed from prostate cancer patients, we develop analytic methods of aggregated distances to identify fiv

141 but is limited by the assumptions of current analytic methods regarding the structure of data.

142 Our goal is to encourage appropriate analytic methods that produce replicable results for stu

143 phasize large-scale analysis--including meta-analytic methods that synthesize hundreds or thousands o

144 The application of traditional analytic methods to the data from such studies can resul

145 tant expansion of the literature in terms of analytic methods used and level of geography studied.

146 studies using standardized sampling, shared analytic methods, and databases, including external vali

147 We extracted data for study characteristics, analytic methods, and key findings, and applied the AMST

148 Large-cohort initiatives and new analytic methods, such as admixture mapping, are current

149 ingle-cell analysis, but current single-cell analytic methods, such as PCR-based strategies or whole-

150 d plasma with newly developed nanobody-based analytic methods.

151 A simplified analytic model demonstrates that heterogeneity in shear

152 verse-variance weighted, random effects meta-analytic model for observational data.

153 Furthermore, an analytic model is developed to understand and precisely

154 A simple analytic model is formulated to predict the transition i

155 An analytic model that accounts for the feedback between me

156 ied by comparison with that obtained from an analytic model that predicts the polarization state on t

157 tivity analyses can be performed to test the analytic model under varying conditions.

158 Patients and Methods A decision-analytic model was built to compare the costs and benefi

159 A decision analytic model was constructed and populated with clinic

160 Materials and Methods A decision-analytic model was constructed to compare cost and effec

161 A decision-analytic model was developed to compare costs for periop

162 A decision analytic model with sensitivity analysis determined the

163 In a path analytic model, cBF volume significantly mediated the as

164 Inputs were loaded into a decision analytic model, with an annual discount rate of 3% appli

165 rch interest, are coherent with the proposed analytic model.

166 ohort cost-effectiveness study with decision analytic modeling and probabilistic sensitivity analysis

167 Decision analytic models are analytical tools that help decision

168 udies to support test adoption used decision-analytic models with assumptions and data derived from d

169 While application specific synthesis and analytic modules and LOC devices are widely described, t

170 Although meta-analytic neuroimaging studies demonstrate a relative lac

171 rony influenced TL in essentially all of our analytic, numerical, randomization-based, and empirical

172 on and integration of chemical synthesis and analytics on small length scales, the development of com

173 , which were estimated empirically and using analytic or microsimulation models.

174 analysis of new questions (72%), followed by analytic or statistical approaches to clinical trials (9

175 techniques and terminology used in decision analytic papers, to provide the reader a practical guide

176 The future perspective for improvement of analytic performance of lactate biosensors are discussed

177 dine with an independent assessment of their analytic performance; this program fosters improvement i

178 ve rim cultures over the last 5 years of the analytic period compared with the first 15 years (P = 0.

179 Two analytic perspectives on environmental assessment domina

180 data and the Tract-Based Spatial Statistics analytic pipeline to first analyze fractional anisotropy

181 Here we have developed a new whole-genome analytic pipeline to optimize ChIP-Seq protocols on pati

182 compartment separately using a prespecified analytic plan for exposures, covariates, effect modifier

183 acquire VWD, and a modular, multi-algorithm analytic platform (ventMAP) to enable automated detectio

184 arch Database issue, GeneWeaver's underlying analytics platform has been enhanced, its number and var

185 osis infection, using a human microarray and analytics platform.

186 No meta-analytic pooling was done.

187 Random effect meta-analytic pooling was performed reporting results as a su

188 d the full MenB vaccination series, limiting analytic power, these data suggest that MenB-FHbp and Me

189 erved data sets, to make recommendations for analytic practice.

190 reach peta-scale level creating storage and analytic problems for large-scale systems biology studie

191 one-stage, individual participant data, meta-analytic procedure was employed using a mixed-effects, m

192 lds, which might be improved by more complex analytic procedures.

193 1) propose general guidelines for predictive analytics projects in psychiatry, (2) provide a conceptu

194 e, ongoing advances in the field of big data analytics promise to create an exciting opportunity to o

195 te analyte losses at different stages of the analytic protocol.

196 to map a spin ensemble to a spring model so analytic pulses can be designed using linear methods.

197 ss data-related problems ranging from simple analytic queries of existing measurement data to the mor

198 ll RNA using published datasets and in-house analytic results.

199 Meta-analytic reverse-inference analysis showed that these re

200 f 14+/-10.2 years, during which clinical and analytic risk factors (including urine sediment examinat

201 cipants (47 886 visits) were included in the analytic sample (2278 HIV-seropositive participants cont

202 Factor analysis of our analytic sample (n = 3,566) established two sub-scales o

203 Among our analytic sample (n = 3,567), 11.4% of respondents report

204 Our analytic sample (N = 62,442) was divided into cohorts on

205 The analytic sample for this study was 1335.

206 and the Dietary Inflammatory Index (DII).The analytic sample included 10,034 women aged 65-84 y with

207 The analytic sample included 131 children with SCA (median a

208 The analytic sample included 181 students (96 boys [53.0%] a

209 The 30-day analytic sample included 31 636 patients, and the 1-year

210 The analytic sample included 4620 participants (mean age, 52

211 The analytic sample included those also completing 1 or more

212 Among the mendelian randomized analytic sample of 184305 individuals (60801 CAD cases [

213 Of the final analytic sample of 9512 enlisted soldiers who attempted

214 The final analytic sample size was 1,124,162 biological children.

215 The median age of the 240-person PROWL-1 analytic sample was 27 years (range, 21-52 years); 49 we

216 The median age of the 271-person PROWL-2 analytic sample was 30 years (range, 21-57 years); 147 w

217 te of initial lumpectomy in the 3729 patient analytic sample was unchanged during the study.

218 iewing and at least one urine drug test (our analytic sample).

219 e data requirements and were included in the analytic sample.

220 CDDCs and 95 from VTCs were included in our analytic sample.

221 surgery type was known constituted the final analytic sample.

222 at both timepoints with complete data in the analytic sample.

223 were excluded, leaving 3729 patients in the analytic sample; 98% of these identified their attending

224 To this end, we first derive a semi-analytic scaling form for R N, which reproduces the limi

225 ation selection procedure (Lasso-PL) and the analytic selection method (Lasso-AL) are fast and powerf

226 ives in positive-ion mode markedly increases analytic sensitivity (low fmol/muL).

227 The higher analytic sensitivity and lower false-negative rate of HT

228 In addition, the increased analytic sensitivity of HTS permitted identification of

229 informatic and artificial intelligence (AI) analytics simply cannot handle.

230 Healthcare-specific analytic software is needed to process the large volumes

231 By the development of blended data analytics software called Xenophile, the identity of the

232 h for Child Health (PERCH) study required an analytic solution appropriate for a case-control design

233 The analytic solutions are obtained with certain approximati

234 The determination of exact analytic solutions of the focusing 1D-NLSE prototyping R

235 allergen molecules has had a major effect on analytic specificity and allergy diagnosis.

236 ested through an investigative, non-judging, analytic stance, a focus on evidence-based practice and

237 ition showing an investigative, non-judging, analytic stance, a focus on evidence-based practice that

238 odologies, interpretation of indicators, and analytic standardization is important for further improv

239 We also consider different analytic strategies for strengthening causal inference.

240 rnative metrics such as urinary flow rate or analytic strategies such as covariate-adjusted standardi

241 genetic data provides a rapid and accessible analytic strategy that can be undertaken using publicly

242 h ethnically matched controls, we devised an analytic strategy to identify and rank potential candida

243 For the main analytic strategy, a linear mixed model was implemented,

244 emiologic research; illustrate the potential analytic strength of the surveillance system and its abi

245 able to understand conclusions from decision analytic studies and are familiar with the specific defi

246 Factor analytic studies provide fairly consistent evidence that

247 Three separate analytic studies were performed to evaluate the accuracy

248 ned synthetic, structural, and spectroscopic/analytic study to estimate the N-H bond strengths of sev

249 et-based bottlenecks through systems biology analytics, such as protein-protein interaction (PPI) net

250 No influence of time points on meta-analytic summary effect estimates was found.

251 Our study provides meta-analytic support to the hypothesis that, in addition to

252 of antiplatelet therapy varied depending on analytic technique, and none were concordant with the re

253 The study designs and analytic techniques applied here form a structured, unbi

254 both the promise and the limitations of the analytic techniques for capturing functional diversity a

255 ects of climate on health, and refinement of analytic techniques for detection and attribution.

256 care efficiently and the importance of using analytic techniques to understand the clinical and econo

257 t differ materially when random-effects meta-analytic techniques were used.

258 Using meta-analytic techniques, we aimed to clarify the relationshi

259 ls, adjusted for sex and education, and meta-analytic techniques.

260 his issue, which requires reliable and rapid analytics techniques for quality assurance.

261 esource constraints, but current genomic and analytic technologies are enabling us to mine this natur

262 amera trapping protocol, and we compute data analytics that correct for imperfect detection.

263 ently have been limited by small samples and analytics that do not evaluate complex multivariate imag

264 portantly, we show quantitatively with LC/MS analytics that the intracellular cargo release is contro

265 In process analytics, the applicability of Raman spectroscopy is re

266 An approximate analytic theory was used to generate explicit formulas f

267 istic simulations, coarse-grained models and analytic theory.

268 ily on intuitive thinking-and decreases when analytic thinking is engaged.

269 ponding to thin films, it is a challenge for analytics to measure the film porosity.

270 o management provides objective insights and analytics to support research and development decision m

271 io-imaging) the ability to query over 12 000 analytic tool descriptions integrated from well-establis

272 Here, we present ePlant, a visual analytic tool for exploring multiple levels of Arabidops

273 f whole-brain networks defined with the meta-analytic tool Neurosynth, we find that neural activity d

274 -TDS was compared to five similar bioscience analytic tool retrieval systems with the Bio-TDS outperf

275 estingly, using a large fMRI sample and meta-analytic tool with Neurosynth, we found that this brain

276 ingle-cell RNA sequencing coupled with a new analytic tool, iterative clustering and guide-gene selec

277 ted motor symptoms, but more broadly for our analytic toolkit in general.

278 esearchers in retrieving the most applicable analytic tools by allowing them to formulate their quest

279 However, current analytic tools do not provide optimal features for analy

280 Our integrated knowledge graph, analytic tools, and web services enable diverse users to

281 tometry, used together with these innovative analytic tools, has the power to lead to key discoveries

282 Two Global Burden of Disease analytic tools, the Cause of Death Ensemble model and Di

283 del, using molecular dynamics and associated analytic tools.

284 onsensus enhancer annotation and integrative analytic tools.

285 Data analytics tools provide rejection of interferences and m

286 purpose of this article is to develop a meta-analytic top scoring pair (MetaKTSP) framework that comb

287 enting this information with I-V data and an analytic transport model, we are able to quantitatively

288 of colon tissue-the patient consented to an analytic treatment interruption (ATI) with frequent clin

289 We present interactive analytics using a cloud-based columnar database built on

290 DFS and MFS for OS by using a two-stage meta-analytic validation model by determining the correlation

291 We performed a series of analytic validation studies to evaluate the performance

292 For example, the analytic variability of serum ferritin measurements acro

293 oth timepoints and had complete data for all analytic variables.

294 merase Chain Reaction) suggest exploring new analytic ways to get reliable results in a short time.

295 optimal conditions can change in abrupt non-analytic ways, depending also on the densities of networ

296 For in situ protein analytics, we developed a multiplex in situ proximity li

297 the use of Raman spectroscopy for real-time analytics when strongly increased sensitivity is require

298 scale monitoring infrastructure and powerful analytics, which can be scaled to incorporate additional

299 alternatives to cluster heatmaps using pair analytics with a computational biologist, and evaluating

300 Our numerical and semi-analytic work underlines that the type of stability meas