ライフサイエンスコーパス: ranking

1 recursor and fragment masses, and annotation ranking.

2 by a single nucleotide alters the stability ranking.

3 city model significantly improves neoantigen ranking.

4 le for the increase in overall raw score and ranking.

5 port with extensive annotation for candidate ranking.

6 ctly interpretable in terms of profitability ranking.

7 i-CRISPRs, we built a model based on XGBoost ranking.

8 ption points to achieve appropriate priority ranking.

9 , and WalletHub.com (r(s) = 0.38, p = 0.006) rankings.

10 ct of quality metric methodology on hospital rankings.

11 News and World Report rankings.

12 and utilization-based outcomes, and hospital rankings.

13 significance to knowledge provided by these rankings.

14 nd Toothbrush.org (r(s) = 0.60, p < 0.00001) rankings.

15 ecific SAARs to quantify effects on hospital rankings.

16 beneficial for the performance of structured rankings.

17 including staff diversity data in university rankings.

18 bstantial movement in hospitals' utilization rankings.

19 had a substantial impact on hospital quality rankings.

20 ociation with patient outcomes, and hospital rankings.

21 ) and Toothbrush.org (r(s) = 0.35, p = 0.01) rankings.

22 her tested methods with the best classifiers ranking 72% of all reported variants and 94% of reported

23 urrence, with a 96% probability of correctly ranking a detect/nondetect pair.

24 tured ridge-tracing method followed by shape ranking according to a trained classifier.

25 We explored whether meal rankings according to postprandial glycemic excursions d

26 ferent CGM devices result in concordant meal rankings according to postprandial glycemic excursions.

27 ogical signal, it should induce similar node rankings across PINs obtained at different reasonable co

28 was the fourth most common cancer in women, ranking after breast cancer (2.1 million cases), colorec

29 a normal mean-based model on a screening and ranking algorithm for copy number variation identificati

30 An R-package, EBrank, implementing the ranking algorithm is available on CRAN.

31 ith the greatest summed intensity using this ranking algorithm were comparable to other lipid identif

32 We develop an Empirical Bayes ranking algorithm, using the marginal distribution of th

33 dicted and prioritized using a network-based ranking algorithm.

34 l supervised as well as unsupervised feature ranking algorithms.

35 A new system based on a score ranking all candidates was implemented in January 2018.

36 Although rankings allow a direct and quantitative comparison of c

37 by half, compared with biomass-productivity ranking alone, with little productivity impact (<1.7% pe

38 Gene rankings also inform the interpretation of COVID-19 GWAS

39 he modeled structure, a scoring function for ranking alternative models based on diverse types of dat

40 Our main findings are that (1) ranking alternatives through direct rating (response tim

41 with over 10 000-14 000 catalytic turnovers, ranking among the most efficient nitrene transfer biocat

42 Using this ranking and exclusion design (R/ED) framework, we modele

43 BEERE (Biomedical Entity Expansion, Ranking and Explorations) is a new web-based data analys

44 gns each variant a p-value to permit variant ranking and prioritization.

45 t" and "worst" performing sets based on this ranking and prospectively validated these sets in a subs

46 Desirability of outcome ranking and response adjusted for duration of antibiotic

47 The ranking and screening of MOS sensors, specific for volat

48 nal screening techniques that aid in feature ranking and selection by accommodating various forms of

49 The clonal hierarchy has distinct ranking and the resultant invariant combinations of domi

50 t constructs a macroinvertebrate sensitivity ranking and, subsequently, a predictive trait model for

51 o examine associations between County Health Rankings and graft and patient survival post-LT.

52 ces by different procedures yields different rankings and that humans appear irrationally impulsive (

53 g good correspondence between the sequences' rankings and their binding affinities.

54 ization of models, new confidence scores for ranking, and links for accessing all annotated model dat

55 hus offers an efficient tool for evaluating, ranking, and optimizing materials with high Li-ion condu

56 The signatures obtained from both the ranking approaches were integrated into two mathematical

57 n these two taxa, as well as their taxonomic ranking are contentious.

58 Nowadays, world rankings are promoted and used by international agencies

59 , affecting millions of people worldwide and ranking as a leading cause of disability for almost thre

60 The primary outcome was national percentile ranking as measured with the survey.

61 The IntFOLD server has established its ranking as one of the best performing publicly available

62 Our PR ranking based approach is useful to rank the phenolics t

63 The ranking based on degree can successfully identify the mo

64 re specifically, we distinguish two kinds of ranking based on the weighted degree decomposition.

65 Rankings based on soil studies show AC first for carbon

66 ethod outperforms both clustering and energy ranking-based methods, all the while consistently offeri

67 first approach compares the distribution of rankings between arms.

68 given the discordance of within-subject meal rankings between simultaneous CGM devices.

69 als were used to compare within-subject meal rankings between the CGM devices according to their incr

70 detrimental to the performance of the random ranking, but they are beneficial for the performance of

71 h as through an analytical approximation, or ranking by copy number and/or KD value, and find that th

72 A ranking by state reveals that GHGs (per unit floor space

73 ore computationally efficient alternative to ranking by their P-values.

74 ities Index (DCI), a composite socioeconomic ranking by ZIP code, will predict risk-adjusted outcomes

75 When comparing hospital rankings by crude proportion to risk-adjusted ranks, 24

76 agreement was found on hospital performance rankings by using the readmission and EDAC measures (wei

77 Hence, the performance of states in global rankings can be assessed based on their development leve

78 f ligands as our target, we show that robust rankings can be produced only through combining ensemble

79 Finally, we show that ranking candidates by their posterior mean value of thei

80 ound 25%-50% or less in many cohorts, a good ranking cannot be taken to imply that the gene or diseas

81 between agents, individual positions in the ranking change more, and the typical structure shows a d

82 form AQuA-HiChIP, going from cell culture to ranking chromatin interactions within 6 d.

83 that infiltrate the plant disguised as high-ranking civilians (transcription factors) to trick the p

84 s as social interactions governing a dynamic ranking, communal work to produce a public good, and nor

85 ancer in prostate needle biopsy samples at a ranking comparable to that of international experts in p

86 me was the change in departmental percentile ranking compared with the overall hospital ranking for p

87 hospitals showed large decline in percentile rankings compared with baseline.

88 d largely through a system of soliciting and ranking competitive grant proposals.

89 ss correlation coefficient (ICC) and patient ranking consistency was assessed using a Spearman's rank

90 thways, and provides the user with necessary ranking criteria such as target yield to decide which ro

91 cise interventions (surface under cumulative ranking curve values [SUCRCV]: 95.6%, standardized mean

92 ses to create a surface under the cumulative ranking curve.

93 by ranking the surface under the cumulative ranking curves (SUCRAs).

94 a were matched to county-level County Health Ranking data using transplant recipient zip code, and na

95 We demonstrate that the type of successful rankings depend on the selection strength, the underlyin

96 The sum of ranking differences (SRD) algorithm can efficiently solv

97 The flexible fusion method of sum of ranking differences (SRD) is applied to combine all asse

98 iscreeTest, a two-step evaluation metric for ranking discretization methods for time-series data.

99 HumanNet performs well in ranking disease-linked gene sets with minimal literature

100 Desirability of outcome ranking (DOOR) is an innovative approach in clinical tri

101 ly, we reported an ensemble-decision aliquot ranking (eDAR) platform for the rare cell and CTC isolat

102 tions, and we introduce a compact index, the Ranking Efficiency Product (REP), to evaluate the effici

103 a 5' thymidine is present in most of the top ranking elements.

104 s oncogene B (ERBB)3 were identified as high-ranking essential kinase hits in the HNSCC cell lines.

105 In gene-ranking experiments, IRT achieves a top-1 accuracy of 50

106 hat our method outperforms previous methods, ranking first among 26 others on CAPRI blind tests.

107 We find that the nodal importance ranking for nonlinear and linear control exhibits opposi

108 e ranking compared with the overall hospital ranking for patient experience measured with a similar s

109 and DDIs were classified by a traffic-light ranking for severity.

110 s work introduces the usage of deep learning ranking for small molecules identification using low-res

111 Within-subject meal rankings for incremental glycemic responses were relativ

112 ial reclassification of hospital performance rankings for mortality and moderate reclassification for

113 Hospital mortality rankings for older patients with AMI inconsistently refl

114 der patients with AMI inconsistently reflect rankings for younger patients.

115 We present methods of ranking formula accuracy, including the new Haigis IOL F

116 tion, scientific literature, and oral health rankings formulated by WalletHub.com and Toothbrush.org.

117 To address this issue, 42 feature ranking (FR) methods are integrated to form a MATLAB too

118 kinetic transport assays on four of the top-ranking genes (EXOC2, EXOC7, PARD6B, and LEPROT) reveale

119 tional overlap of two diseases using the top-ranking genes and the associated enrichment of biologica

120 We have previously proposed an approach for ranking genes based on methylation discordance within th

121 Top ranking genes with the highest game theoretic centrality

122 utational tool for statistically testing and ranking genomic features of interest based on observed D

123 We show that random ranking has generally little ability to successfully ide

124 Our highly ranking hits included a short list of interferon-stimula

125 studies support a facile method for affinity-ranking hits.

126 We develop this Informer-Based-Ranking (IBR) approach using the Published Kinase Inhibi

127 Imaging system ranking illustrated that the use of point-spread functio

128 to 93.6 of 100 (P < .001), and the national ranking improved from the 35th to 50th percentile (P = .

129 rm acute care hospitals in the United States ranking in either the lowest or highest quartile of risk

130 C are the best suited methods for hypothesis ranking in LBD, but there is value in having a variety o

131 ted subsets on a 2D grid with property based ranking in one dimension and increasing structural redun

132 t experience improvement program on national ranking in patient experience in a large academic radiol

133 teracted with humans the most, and that high-ranking individuals initiated more interactions with hum

134 l stress, such as being in proximity to high-ranking individuals, or non-friends.

135 ept when the underlying evolutionary model's ranking-intensity parameter, alpha, is chosen to be larg

136 The ranking is based on the relative change in bound ligand

137 If ranking is constrained, thus leading to bounded score di

138 The step of ranking is intuitively natural for scRNA-seq data and pr

139 When ranking is unconstrained, we observe a high concentratio

140 Specificity of small ions, the Hofmeister ranking, is long-known and has many applications includi

141 rom different techniques, and their relative ranking, is not straightforward, as the interactions bet

142 Machine learning ranking (learning to rank) is a class of machine learnin

143 n be crucial in the interpretation of global rankings, making comparison between countries more signi

144 t-copulatory reproductive senescence in high-ranking male nonhuman primates.

145 ariation in the reproductive success of high-ranking male rhesus macaques on Cayo Santiago.

146 otic' social structure) in which the highest ranking male willow tit is fourth in the overall hierarc

147 Alpha males, the highest ranking males in a social group, are predicted to have b

148 rating genetic relatedness revealed that low-ranking males in large coalitions were typically related

149 Older high-ranking males in stable groups had fewer offspring than

150 groups had fewer offspring than younger high-ranking males in stable groups in 2013.

151 the Nazi era and on the involvement of high-ranking members in medical crimes.

152 Further annotation of top-ranking metabolic features nominated by the trained mode

153 The ranking method involves varying the receptor-to-ligand c

154 ed by using a machine learning-based feature ranking method to identify a small set of top-ranked pre

155 esults indicate that, regardless of the seed ranking method used, sequential seeding strategies deliv

156 A score ranking method was developed to determine the best predi

157 abolomics is linked to the lack of efficient ranking methods allowing accurate identification of meta

158 parison between several different hypothesis ranking methods for LBD, and compare them against our pr

159 al experiments using four well-known feature ranking methods from the machine learning field and five

160 ing P-values and a number of other competing ranking methods.

161 are much more common for one of the feature ranking methods.

162 sets, we demonstrate that CERNO is robust to ranking metrics, as well as sample and GS size.

163 The deep learning ranking model outperforms other approaches and enables r

164 ied to construct a ligand-based multi-filter ranking model to distinguish between confirmed PPAR-delt

165 and successfully tested a handful of the top-ranking molecules in C. elegans survival assays and achi

166 Of these compounds, 38 high-ranking molecules were synthesized and tested, revealing

167 From the top-ranking molecules, 44 and 549 compounds were synthesized

168 ion molecules by this model picked ~2500 top ranking molecules.

169 ency, graduating from a U.S. medical school, ranking more programs, and having a higher percentage of

170 istic (ROC) curve (AUC); the Mean Reciprocal Ranking (MRR) of pathway prediction reached 0.67.

171 om network's internal structural similarity, ranking networks on a continuous scale from crystalline,

172 A ranking of 1 signifies that both the lipid class and add

173 tional advantage that there is no artificial ranking of 128 journals in the category but rather an at

174 l standard and target analyte match, while a ranking of 3 signifies that neither the adduct or class

175 dynamics methodology, for the evaluation and ranking of agents in large-scale multi-agent interaction

176 cells from a human glioblastoma dataset, the ranking of biologically relevant genes and pathways show

177 The ranking of catalysts by (Z)-stilbene isomerization initi

178 e concept of metagene entropy and allows the ranking of cells based on their differentiation potentia

179 he most common tests result in a qualitative ranking of film survival, not a measurement with scienti

180 representative of true differences, and poor ranking of genes by effect size.

181 ustment of multiple hypothesis tests and the ranking of genomic features based on their statistical s

182 Ordinal ranking of glaucoma outcomes based on preference weights

183 uctural features of GO, (II) structure-based ranking of GO-terms, (III) mapping to reduced GO-DAGs in

184 Here we present a dynamic ranking of host genes implicated in human betacoronaviru

185 A ranking of important variables in identifying subjects a

186 se human DNA, revealing a strikingly similar ranking of influential TFs and providing additional supp

187 Finally, we provide a ranking of key antibiotics by their estimated population

188 he final analysis focuses on a P-value-based ranking of locations which might then be investigated fu

189 equency by mutability significantly improved ranking of mutations and driver mutation prediction.

190 In Patagonia, the ranking of natural variability of drivers is as follows:

191 Monkeys can learn the implied ranking of pairs of images drawn from an ordered set, de

192 Consensus ranking of protein affinity to identify point mutations

193 elagic and benthic pathways revealed similar ranking of species dependency over 4 years, but annual v

194 ived from the experimental data improves the ranking of structures.

195 ter-stress constraints to productivity-based ranking of suitable sites reduces water-stress impact by

196 ression (GTEx), generating robust importance ranking of TF effects and interactions.

197 aired species impurities but not the quality ranking of the clones.

198 It allows to get a fair ranking of the coating performances toward protein adsor

199 The IZ is a ranking of tissue areas by their distance to the tumor e

200 The ranking of uncertainty sources was quite different at th

201 It can be used for the evaluation and ranking of virtually any coating (neutral or charged) in

202 ivity and Cyp1a4 mRNA expression allowed the ranking of wetland sites based on aryl hydrocarbon recep

203 The hierarchical rankings of primary immunization route with respect to e

204 ConSReg provided better rankings of the correct transcription factors in 61.7% o

205 n management, which in turn affect genotypic rankings of transpiration in a time-dependent manner.

206 arning algorithms that perform a comparison (ranking) of objects.

207 children, in a country with an above-average ranking on gender parity.

208 n ASEs were instrumental to our second place ranking on Template Based Modeling (TBM) and Free Modeli

209 ants and perform gene-specific variant score ranking on the population level.

210 ct the optimal set of genes from the highest-ranking ones.

211 For mid-ranking, or mesopredators, differences in habitat use mi

212 ions of ages for each individual, based on a ranking order of individuals from youngest to oldest and

213 analysis, such as analyzing total events and ranking outcomes.

214 alpha-Rank automatically provides a ranking over the set of agents under evaluation and prov

215 itals showed large improvement in percentile rankings over time and a similar proportion (23.7%) of t

216 ent with the networking structure of the top ranking pairs.

217 In the overall ranking Pathway Analysis with Down-weighting of Overlapp

218 hly correlated with lower monthly percentile ranking (Pearson correlation coefficient of -0.69; P = .

219 tion strength is weak, while more structured rankings perform better at strong selection.

220 ti-female groups, and males compete for high ranking positions.

221 water model yielded the highest scoring and ranking power compared to the others.

222 ixing the receptor atoms improved scoring or ranking power.

223 earch exists on how habitat selection of mid-ranking predators can influence population-level process

224 enrichment of real interactions for the top-ranking predicted interactions, as shown by cosubcellula

225 eighborhoods yield higher precision for high-ranking predictions than RBM when no information regardi

226 Based on the ranking probabilities, motor relearning programme was ra

227 to evaluate them as a classification task or ranking problem, none have systematically investigated t

228 and reveals a promising complementary way of ranking putative crystal structures.

229 The DOOR endpoint fitting these rankings (r = 0.89; 95% confidence interval, 0.67 to 0.9

230 pment as well as income inequality, on 2 top-ranking regional priorities for adolescent nutrition and

231 Concerning divergent rankings reported in the literature, the great sensitivi

232 e best (Spearman 0.797 and 0.794 with expert rankings, respectively).

233 ields provided the most accurate scoring and ranking results.

234 Results: Feature ranking revealed that the gray-level cooccurrence matrix

235 feature representations, and (ii) A flexible ranking scheme with the ability to integrate external va

236 how gene- and population-calibrated variant ranking scores can improve epilepsy variant prioritizati

237 term-within the user input by computing the ranking scores of all entities.

238 e generated from the analysis; the ranks and ranking scores reported with statistical significance fo

239 the challenge of arriving at a consensus on rankings/scorings.

240 Furthermore, mutation ranking showed the possibility of finding new resistance

241 re sensitive to abundance changes than other ranking statistics.

242 The robust ranking step performed on Medical Subject Headings (MeSH

243 Using various ranking strategies including a range of parameters, we f

244 We show that a ranking strategy based on negative-weighted degree allow

245 aders in the case of weak selection, while a ranking strategy based on positive-weighted degree perfo

246 less than 50% (surface under the cumulative ranking (SUCRA)/heterogeneity (vague)/n: 0.77/0.14/3).

247 LMN uses a ranking system (1-3) to assign lipid standards to target

248 Conclusion A simple ranking system based on interinstitutional variation in

249 The results of this ranking system clarify disparities between the studies.

250 RefFinder, a comprehensive ranking system integrating all four above-mentioned algo

251 by the completeness of their data based on a ranking system using five criteria: sample collection, s

252 and off-target scoring predictions into its ranking system, and nominates secondary nicking sgRNAs f

253 Finally, a ranking technique is developed based on PageRank (PR) al

254 Bayesian ranking techniques may offer a solution to this problem

255 Precision and recall curves are generated by ranking term pairs and applying a threshold at each rank

256 A sensory ranking test was also performed on ripened nectarines to

257 erimental treatment would have a better DOOR ranking than if assigned to control was estimated.

258 uire a known reference ligand and produces a ranking that is insensitive to variations in the concent

259 porating bullying records into institutional rankings) that accelerate successful responses to academ

260 free, whereas MAUT and ELECTRE III agreed on ranking the "least worst" choices.

261 oncentrations and higher resolutions favored ranking the correct formula in the top 10.

262 study is to develop tools for assessing and ranking the enzymolysis kinetics of dimethacrylate (DMA)

263 Using the assay allowed ranking the hazard potential of environmental pollutants

264 Methods for ranking the importance of nodes in a network have a rich

265 ex, cognitive interviews and quantifying and ranking the items to determine the usability of the ques

266 RANKCORR proceeds by ranking the mRNA counts data before linearly separating

267 ers collaborated as citizen scientists, each ranking the performance of three varieties randomly assi

268 veloped based on PageRank (PR) algorithm for ranking the phenolics.

269 mean differences (MDs) with 95% CIs, and by ranking the surface under the cumulative ranking curves

270 Robert Wood Johnson Foundation County Health Rankings, the United States Renal Data System, and the S

271 o genetic inactivation provides a metric for ranking their relative importance for bacterial replicat

272 D-DNP NMR-derived ranking, therefore, is capable of determining the ligand

273 n be manually reviewed, making automatically ranking these hypotheses critical.

274 extract important insight underlying global rankings, thus adding value and significance to knowledg

275 and precision medicine, and thus, automatic ranking to figure out the most informative and discrimin

276 ct a gene ontology-based semantic similarity ranking to find suitable synergistic cotargets for netwo

277 NA aptamer motifs and uses a simple weighted ranking to order the candidate aptamers, all driven with

278 In this study, a recently established hazard ranking tool for alternatives assessment based on in sil

279 ations and experimental pilots in accurately ranking treatments.

280 , PairedFB has overall better performance in ranking true differentially expressed genes (DEGs) on th

281 istency of monthly district-level prevalence ranking using Kendall's correlation coefficient.

282 Defining the best SRD ranking value (threshold) for determining class membersh

283 However, this SRD ranking value is automatically optimized by using a rece

284 High-ranking variant allele fractions implicated ZNF750, PIK3

285 In additional 7,551 cattle, the high FAETH-ranking variants had significantly increased genetic var

286 production traits compared to the low FAETH-ranking variants.

287 activated (VTA) in normative atlas space and ranking voxel-wise for outcome distribution.

288 Gene stability ranking was assessed using coefficient of variation (CoV

289 This ranking was reflected in increasing delta(15)N values in

290 DIAAS ranking was thus essentially driven by the amino acid co

291 The in vitro hazard ranking was validated in mouse lungs by oropharyngeal in

292 Blinded to practice rankings, we conducted site visits at four highly ranked

293 pplied to classical computing tasks, such as ranking webpages and solving the Schrodinger equation in

294 pient zip code, and nationwide County Health Rankings were created.

295 s and percentage of pairwise agreement among rankings were estimated to inform development of a DOOR

296 While percentile rankings were generally consistent over time at ~45% of

297 tion, and safety were ranked lower (although rankings were still considerably high).

298 e to surprising robustness crossovers and re-rankings, which can have significant implications for de

299 se and compared by state firearm legislation rankings with respect to FFR.

300 arge N balance were identified in specific ("ranking") years, and these same fields were assessed in