ライフサイエンスコーパス: correctly predict

1 asuring the fraction of trophic relations it correctly predicts.

2 statistics on L and myosin concentration is correctly predicted.

3 Sixteen of the 17 mutants were correctly predicted.

4 s covered with ruthenium monolayers are also correctly predicted.

5 tion, beta-pinene, the signs of [alpha]D are correctly predicted.

6 ain at least one SFP probe, at least 80% are correctly predicted.

7 ides, about 70% of the native base-pairs are correctly predicted.

8 al validation set, 90% of all molecules were correctly predicted.

9 l test set, 70.3% of positive TdP drugs were correctly predicted.

10 ring calibration and cross-validation and to correctly predict 100% of oxyphil and 99.8% of chief cel

11 d temporal cortex obtained early in recovery correctly predicted 20 of 22 subjects who did not relaps

12 ated pedigrees and three extended pedigrees, correctly predicting 20% more fourth- through ninth-degr

13 The original CHOP ROP model correctly predicted 452 of 459 infants who developed typ

14 genetically unrelated, in simulations, PADRE correctly predicted 50% of 13(th)-degree relationships t

15 subvalidations using this training data set correctly predicted 58% of inhibitors when analyzing act

16 asthma duration, and blood neutrophil counts correctly predicted 64% of sputum neutrophil percentages

17 The gene-specific CNV model from AT correctly predicted 67% (P = 0.041) cases for relapse an

18 ally deleted per fold showed that the method correctly predicts 68% of the deleted edges on average.

19 predicted, but not blood eosinophil counts, correctly predicted 69% of sputum eosinophil percentages

20 kbones, FASPR achieved a good performance by correctly predicting 69.1% of all the side-chain dihedra

21 ne-specific CNV from tumor, the genome model correctly predicted 73% (receiver operating characterist

22 Our method correctly predicts 73% of species richness.

23 edian-sized CNV from tumor, the genome model correctly predicted 75% (P < 0.001) cases for relapse an

24 Furthermore, the model correctly predicted 79% of the existing shallow groundwa

25 Our models correctly predicted 80 to 90% of elections in out-of-sam

26 edian-sized CNV from blood, the genome model correctly predicted 81% (P < 0.001) cases for relapse an

27 under constraints on the folding free energy correctly predicted 83% of amino acid residues (94% simi

28 The 2013 Fuzzy Forests model also correctly predicted 86% of good health outcomes using 20

29 ively accrued validation set, the classifier correctly predicted 88% of responders and 83% of nonresp

30 The model correctly predicts 92% of occurrences observed outside o

31 optimized and validated acetaminophen model correctly predicted 98.2%, and the ibuprofen model corre

32 tly predicted 98.2%, and the ibuprofen model correctly predicted 99.0% of the urine specimens contain

33 , the results of comparative transcriptomics correctly predicted a 2AA-dependent motility defect and

34 pletion and un-blinding, the biomarker assay correctly predicted a clinical response in over 90% of t

35 A score of 2 or above correctly predicted a low arousal threshold in 84.1% of

36 rmed by surgeons of mixed experience levels, correctly predicted a pathologically negative neck in 96

37 This model also correctly predicts a plateau-like response of translatio

38 energies associated with each catalytic step correctly predicts a slight bias towards CO(2) reduction

39 GERV correctly predicts a validated causal variant among link

40 ChIP-Seq data in three mouse cell lines and correctly predicted active and inactive promoters with p

41 Models trained on the dataset correctly predict activity of evolutionarily divergent r

42 est that additional information is needed to correctly predict Alefacept-mediated bridge formation.

43 FimTyper correctly predicted all 42 fimH subtypes from the Sanger

44 It correctly predicts all mutations (functional and permiss

45 reover, retention of WASP together with SCAR correctly predicts alpha-motility in disease-causing chy

46 rthermore, it achieved better performance in correctly predicting ambiguous cellular subtype labels a

47 r, 45 different serotypes or serogroups were correctly predicted among the 196 resolvable isolates, w

48 validation, the EGFR pathway-based signature correctly predicted anti-EGFR treatment response in eigh

49 ructures in the mass range of 120-500 Da and correctly predicted approximately 70% of the individual

50 f four, three of three, and one of two cases correctly predicted as no adhesion, partial adhesion, an

51 the known best ligands for each target were correctly predicted as top ranked, followed by 66%, 76%,

52 remaining adjustable parameters, the theory correctly predicts aspects of the fracture-resistant, wa

53 Using only ESTs we were able to correctly predict at least one splice form exactly corre

54 y score that predicts the expected number of correctly predicted base pairs.

55 (autopodium present and absent) can often be correctly predicted based on Hoxa-13 sequences.

56 emerging after optogenetic stimulation both correctly predicted behavior and resembled natural inter

57 Notably, reaction outcomes were correctly predicted by a simple thermodynamic formalism

58 Seizure outcome following resection was correctly predicted by EEG-fMRI GM in 8 of 20 patients,

59 a ring current is observed, its direction is correctly predicted by Huckel's rule.

60 tumors; 17 (94%) of 18 patients with LS were correctly predicted by IHC.

61 Al(3)O(4)(+) upon Fe-substitution, which is correctly predicted by multireference (MR) wave function

62 y WBS were negative (47%), all of which were correctly predicted by negative (124)I PET/CT.

63 lue for the fraction of trophic interactions correctly predicted by the ADBM, or any other model, wit

64 ME-model, 80% of the upregulated genes were correctly predicted by the ME-model, and ii) that these

65 ll as the most penetrating particle size are correctly predicted by the model.

66 om temperature and daily controlled: 97% was correctly predicted by the model.

67 ler-Lyer stimulus and its major variants are correctly predicted by the probability distributions of

68 keeps 98% of RefSeq gene structures that are correctly predicted by TWINSCAN when removing 26% of pre

69 The modeling correctly predicted cell lines' growth rates, tumor lipi

70 al groups of input cytokine combinations and correctly predicts cell population response to new input

71 Facilitated-transport model can correctly predict cellular iron efflux and is essential

72 articipate in backbone hydrogen bonding than correctly predicted Coils.

73 roblasts to mechanical cues was critical for correctly predicting collagen alignment in infarct scar.

74 compares well with experimental results and correctly predicts column order and back pressure effect

75 e HOMO-LUMO gap (referred to as M-functions) correctly predicts conductance ratios of molecules with

76 We considered correctly predicted contacts and compared their properti

77 TS predictions together, the total number of correctly predicted contacts in the Hard proteins will i

78 DCA is shown to yield a large number of correctly predicted contacts, recapitulating the global

79 A six-gene model was used to correctly predict dasatinib sensitivity in 11 out of 12

80 These criteria correctly predicted death or serious respiratory morbidi

81 The meganv2.1 model correctly predicted diurnal variations in fluxes driven

82 The ORSO recommendation system correctly predicted early data point sources as embryoni

83 We further use our sensor to correctly predict efficient processing of the glycoprote

84 In a proof of concept, our sensor correctly predicts efficient processing of the GPC of th

85 However, current nucleation theories do not correctly predict either the observed nucleation rates o

86 el succeeded in two real-life MetID tasks by correctly predicting elution order of Phase I metabolite

87 tringent specificity level of 99.98%, we can correctly predict enzyme functions for 80.55% of the pro

88 tical model that combines these observations correctly predicts every complete deglaciation of the pa

89 The models were found to correctly predict experimental data and provide an intui

90 Our model correctly predicts experiments near these points and sug

91 this level, favored endo-phenyl isomers are correctly predicted for styrene reactions, but the calcu

92 ensitive to solvation effects, and these are correctly predicted for the first time including those o

93 success rate where all four categories were correctly predicted for ~80% of the compounds.

94 Whether a low-energy cage is isolated can be correctly predicted from the thermodynamic preference ob

95 Comparative genomics has correctly predicted functions for many such genes by ana

96 t to interpret and highly subjective and can correctly predict furcation invasions only approximately

97 Biosciences or MinION sequencing platforms, correctly predicting gene structure, and capturing genes

98 nome assembly and creating a full catalog of correctly predicted genes.

99 using meals logged by the Israeli cohort to correctly predict glycemic responses in the Midwestern c

100 efined genome-scale metabolic model that can correctly predict growth viability over 69 source metabo

101 This is critical for correctly predicting growth yields, contrasting multiple

102 at the simplified GC model and the new model correctly predict haemodynamic and renal excretory respo

103 Our model also correctly predicts higher infection rates among disadvan

104 or two imaging parameters (P < .01), thereby correctly predicting histologic results in 95% (18 of 19

105 This novel algorithm is shown to both correctly predict homeostasis in synaptic weights and so

106 rounded in data from birds and mammals, that correctly predicts how growing animals allocate food ene

107 Finally, the model correctly predicts how lesions in the feed forward loop

108 Finally, the model correctly predicts how PPI depends on pulse intensity.

109 apture effects upon molecular function often correctly predict human (OMIM) and animal (OMIA) Mendeli

110 model that makes center-of-gravity fixations correctly predict human eye movements.

111 The SVM classifier can be used to correctly predict human, mouse and rat piRNAs, with over

112 in CYP2C19, as recommended by the FDA, only correctly predicted if a patient would respond to clopid

113 Based on subnetwork connectivity, we can correctly "predict" if a disease is age-related and prio

114 cts essentiality with an accuracy of 83% and correctly predicts improvements in growth under increase

115 t, we used our in vitro and model results to correctly predict in vivo information capacity and inter

116 Graft outcome was correctly predicted in 27 of 29 BKVN patients by either

117 Susceptibility and resistance were correctly predicted in 87% and 95% of cases, respectivel

118 ection of the change in binding affinity was correctly predicted in a majority of the cases, and agre

119 Clot time is correctly predicted in individual cases, and some models

120 FA status was correctly predicted in the replication cohort with an ac

121 The in vitro binding assay correctly predicted in vivo uptake in a mouse liver mode

122 This measure correctly predicts in situ hybridization patterns for ma

123 These models correctly predicted increased expression of Ech hydrogen

124 Abnormal hippocampal activity correctly predicted individual patient diagnostic status

125 coverage of actual interfaces (percentage of correctly predicted interface residues in actual interfa

126 uracy in predicted interfaces (percentage of correctly predicted interface residues in the predicted

127 The location of the hot spot was correctly predicted irrespective of the protein conforma

128 us electrophilic sites within a molecule and correctly predict isomeric distributions.

129 ortant proteins: caspase-1, CheY, and h-Ras, correctly predicting key allosteric interactions, whose

130 ecular complexes must all be incorporated to correctly predict large-scale behavior in the actin-base

131 deling receptor flexibility is important for correctly predicting ligand binding, it still remains ch

132 dly simulated a virus with similar features, correctly predicting many human behaviors later observed

133 The model correctly predicted MDRR activities for 82.2% of 185 com

134 The LR model correctly predicts methane occurrence in 89.8% (n = 234

135 Overall, IOPTH correctly predicted MGD in only 22%.

136 A dynamic parathyroid CT correctly predicted multiglandular disease in 1 of 7 pat

137 patients (14%), while sestamibi scintigraphy correctly predicted multiglandular disease in 8 of 23 pa

138 sensitive targets of ubiquitin depletion and correctly predict multiple effects of modulating additio

139 Ability of MMRpro to correctly predict mutation carrier status, as measured b

140 The map correctly predicted Nova's effect to inhibit or enhance

141 rate that this extended motif can be used to correctly predict novel targets for SUMO modification.

142 ly, the integrated kinetic model was used to correctly predict observed abundances of H3K27-K36 methy

143 coring system reached an accuracy of 75% for correctly predicting occurrence or nonoccurrence of majo

144 Importantly, this fall correctly predicted operative success in 100% of patient

145 f gland resection and in all cases this fall correctly predicted operative success.

146 eveals a new characteristic time scale which correctly predicts order 10,000-fold speed-up of chemica

147 The model correctly predicted OS distributions in each arm as well

148 cho Brahe in 1601, and the serving algorithm correctly predicts other planetary orbits, including par

149 udes the elastic energy of the membranes and correctly predicts our findings both quantitatively and

150 When operon structures are correctly predicted, our algorithm can predict 81% of kn

151 Luminex serum analysis was able to correctly predict outcomes of 95% of T and B cell FLXM.

152 AMOEBA correctly predicted over 80% of the observed NOEs for al

153 nalyzed the decoys in terms of the number of correctly predicted pair conformations in the decoys.

154 We termed the fraction of correctly predicted pairs (RMSD at the interface of less

155 dysfunction, a positive kidney biopsy should correctly predict pancreas rejection in 86% of the insta

156 works in silico, selecting for networks that correctly predict particular phases of the day under lig

157 MAPPIN also correctly predicts pathogenicity for 87.3% of mutations

158 key features of wild-type pattern formation, correctly predicts patterning defects in multiple mutant

159 oss the modality of reproduction and that it correctly predicted perceptual discrimination.

160 ifying entire kernels based on the number of correctly predicted pixels, improved results were achiev

161 odposin-based receptor homology model, which correctly predicted potent agonism of UDP-fructose, UDP-

162 The probability of correctly predicting presence was low, peaking at 0.5 fo

163 More importantly, this model also correctly predicted previously unidentified binding site

164 This computational method correctly predicts rank order experimental permeability

165 In some cases FABS-NC(') produces over half correctly predicted ranking experiment trials than FABS-

166 ETM correctly predicts regio- and stereoselectivity for a br

167 In the validation set, the model correctly predicted risk category in 52.5% (248 of 472).

168 The results show that RPI-Pred can correctly predict RNA-protein interaction pairs with app

169 ent and permanent repressions, the ENR model correctly predicts several key features of this regulato

170 quired to generate correct auxin patterning; correctly predicts shoot to root auxin flux, auxin patte

171 ne-complex-out cross-validation accuracy and correctly predict SMISPs of known PPI inhibitors not in

172 ected areas in the world, it is important to correctly predict SOC dynamics in salt-affected soils.

173 S-Filter correctly predicts specificity determinants that were de

174 average of 10% more annotated microRNAs, and correctly predicts substantially more microRNAs with onl

175 elop an allergy diagnostic method that could correctly predict symptomatic peanut allergy by using pe

176 nference are desirable because even a single correctly predicted tertiary contact can potentially mak

177 XenoSite correctly predicts test molecule's sites of glucoronidat

178 Importantly, the results correctly predict that affinity will increase as a resul

179 tumorigenic U87PTEN cells were then used to correctly predict that stable EGFR signaling occurs for

180 We correctly predicted that 8 intensive-care beds and 7 ven

181 Notably, the simulations correctly predicted that blocking PFKFB3 normalizes the

182 specifically model mutation information, it correctly predicted that BRAF mutant cell lines would be

183 The design method also correctly predicted that reusing identical ribosome bind

184 Computational experiments correctly predicted that selected kinase inhibitors used

185 kes-all cholinergic responses, and the model correctly predicted that the network would function as a

186 alysis of additional ebolavirus isolates and correctly predicted that the newly identified ebolavirus

187 Importantly, this model correctly predicted that the response magnitude is indep

188 eLAMP correctly predicted that the two tested primer sets woul

189 ulation of the model captures clustering and correctly predicts that (i) essential gene clusters are

190 As such, the model correctly predicts that hippocampal involvement in class

191 simulates GTM tracking and stabilization and correctly predicts that its assembly at a single site co

192 In addition, the model correctly predicts that protecting/denaturing osmolytes

193 veated ideal observer with a central scotoma correctly predicts that the human optimal point of fixat

194 the experimentally validated in silico model correctly predicts that they are not.

195 The theory also correctly predicts that urgency signals in the brain sho

196 idation, we show that the resulting networks correctly predict the (de)-activated functional connecti

197 Notably, the classifier could correctly predict the cancer type in non-TCGA datasets f

198 t an alarming rate, highlighting the need to correctly predict the development of this disease in ord

199 t-descent paths in mass-weighted coordinates correctly predict the direction of the isotope effects,

200 l-Marcus (RRKM)-master equation calculations correctly predict the direction of the trend in selectiv

201 d, partially loop-inserted, prelatent state; correctly predict the effects of PAI-1 mutations on the

202 Quantum-chemical calculations correctly predict the experimental spectroscopic respons

203 intensities and habitat matches are able to correctly predict the identity of the next invading mari

204 on of these lineage-specific microRNAs could correctly predict the lineage of B-cell malignancies in

205 Theoretical calculations correctly predict the most active catalyst and suggest t

206 tive agreement with experimental results and correctly predict the negative response behavior observe

207 rthermore, using this model, we were able to correctly predict the outcome in another patient after 1

208 rved kinetic features of clozapine block and correctly predict the overall affinity and apparent nons

209 ke-Ernzerhof exchange correlation functional correctly predict the palladium porphine (PdP) low-spin

210 Computations correctly predict the preferred site of attack observed

211 le elevated MMP-13 serum levels were able to correctly predict the presence of active bone disease.

212 interactions between birds are sufficient to correctly predict the propagation of order throughout en

213 Bailar and Ray-Dutt transition states, which correctly predict the relative kinetic barriers of compl

214 d microwave conductivity measurements, which correctly predict the relative magnitudes of the convers

215 d on an idealized model beta-hairpin peptide correctly predict the vibrational coupling patterns.

216 Here we show that our method correctly predicted the absence of El Nino events in 201

217 dentified unique transcriptional codes which correctly predicted the cause of many congenital disorde

218 The four-body scoring function correctly predicted the changes to the stability of 169

219 The DAT correctly predicted the development, or not, of AHA afte

220 Computational models correctly predicted the diastereoselectivity of antagoni

221 Thus, constructed population of models correctly predicted the drug effects and occurrence of a

222 Third, the model correctly predicted the dynamics of extracellular lactat

223 combined method, CryptSplice, identified and correctly predicted the effect of 18 of 21 (86%) known s

224 ered from the initial clinical diagnosis and correctly predicted the eventual diagnosis as the clinic

225 The coculture model correctly predicted the exchange of both H2 and formate

226 The model correctly predicted the key PAP-1-sensing residues in th

227 fier based on this gene expression signature correctly predicted the likelihood of progression of sup

228 The AMD pharmacokinetics model correctly predicted the measured serum ranibizumab conce

229 The ANN correctly predicted the N stage in 99.2% of cases, compa

230 cutoff of >=1.50 diopters (D) in either eye correctly predicted the need for glasses 93% of the time

231 The model correctly predicted the observed fractionation of petrol

232 Furthermore it correctly predicted the outcome for 85/102 (83%) NB pati

233 a set in a leave-one-out prediction strategy correctly predicted the outcome for 90% of the samples.

234 l accurately reproduced these data, and also correctly predicted the possible emergence of a split sl

235 tion function of its five isoforms, but also correctly predicted the precise direction of the regulat

236 and high-likelihood PAS and Alvarado scores correctly predicted the presence of appendicitis in 61.1

237 With an accuracy of 77%, the model correctly predicted the presence/absence of an alien spe

238 The model not only correctly predicted the relative signaling potencies of

239 Finally, the model correctly predicted the SCN lesion phenotype in squirrel

240 The docking of the high-energy intermediates correctly predicted the stereoselectivities for 18 of th

241 We correctly predicted the structure of a N-aryl peptoid tr

242 olving populations, we showed that the model correctly predicted the success of the two most benefici

243 Fourth, the model correctly predicted the temporal dynamics of tissue lact

244 On most trials, the cue correctly predicted the upcoming stimulus.

245 An additional pre-cue (S1) correctly predicted the weight in 75% of the trials.

246 ategies showed a very poor performance of in correctly predicting the considered parameters within th

247 faithfully captures the scaling behaviour by correctly predicting the critical exponent of the dynami

248 Correctly predicting the disulfide bond topology in a pr

249 In addition to correctly predicting the divergent pattern of cell sizes

250 buting factors in the hydantoin series while correctly predicting the experimentally observed oxidati

251 pful clinical algorithm to aid clinicians in correctly predicting the genetic basis of various forms

252 We confirmed this by correctly predicting the LDC activity of a DABA DC homol

253 We show that our model is capable of correctly predicting the phenotype of the majority of mu

254 tween mouse lines and validated the model by correctly predicting the repeat length of a blinded mous

255 Our method is capable of correctly predicting the respective metabolic pathway cl

256 The convergent rule correctly predicts the affected loops in every case.

257 compete profiles for diverse RBPs, our model correctly predicts the binding affinities of held-out pr

258 r-law response theory with a plastic element correctly predicts the cell behaviour under cyclic loadi

259 cytes, HEK293 cells and hippocampal neurons; correctly predicts the dose-dependent activation of GIRK

260 This model correctly predicts the effects of inhibiting cell growth

261 d activation; and (5) the mathematical model correctly predicts the existence of at least one protein

262 the observed behavior, our stochastic model correctly predicts the experimental dynamics without any

263 The present model correctly predicts the experimentally observed two-state

264 The model correctly predicts the expression patterns of mutations

265 A CFD model with a flagellar vane correctly predicts the filtration rate of D. grandis, an

266 An algorithm implemented in Rosetta correctly predicts the folding capabilities of the 17-re

267 A minimal model correctly predicts the increased gene expression variabi

268 stabilization, and we show that this method correctly predicts the location of a stabilizing PEGylat

269 The algorithm correctly predicts the major product for about 90% of th

270 e of tetracyanoethene, the maximin principle correctly predicts the most common dimer crystal packing

271 The model correctly predicts the observed honeycomb architecture o

272 segregation based on conformational entropy correctly predicts the positioning of the replication te

273 two field sites demonstrate that our theory correctly predicts the size of the smallest valleys with

274 As a result, our method correctly predicts the spatially dependent diffuse refle

275 Although this magnetostrophic theory correctly predicts the strength of Earth's magnetic fiel

276 We show that the KPL-IFF model correctly predicts the T-cell response to antigen copres

277 The model correctly predicts the time to exclusion observed in exp

278 Mogrify correctly predicts the transcription factors used in kno

279 Furthermore, the model correctly predicts the transcriptional dynamics of cells

280 Our model correctly predicts the urinary beta(2) -m, RBP4 and alph

281 x mechanism using a computational model that correctly predicts the wild-type dynamics of BR expressi

282 The model correctly predicted these results and outperformed an al

283 y RNA sequencing had a suboptimal ability to correctly predict those individuals resistant to convent

284 Finally, modulatory profiling of compounds correctly predicted three previously uncharacterized com

285 The Gusev crater site was correctly predicted to be a low-relief surface that was

286 tumor measurements initially increased were correctly predicted to be responders with SHAPE and subh

287 itive predictive value (PPV) of the peptides correctly predicted to bind very strongly (i.e., K (d) <

288 Strikingly, 55% of the patients could be correctly predicted to have recurrence 13 months (on ave

289 Vessel tortuosity measurements enabled us to correctly predict treatment failure 1-2 months earlier t

290 mbination therapies is therefore crucial for correctly predicting treatment outcomes.

291 the test set of TATA promoters, the program correctly predicted TSS for 35 out of 40 (87.5%) genes w

292 DGE-NET correctly predicts various drug-disease indications by l

293 For this test set, our algorithm correctly predicts water mediation/displacement in appro

294 For this training set, our algorithm correctly predicts water mediation/displacement in appro

295 Our best algorithm was able to correctly predict whether an outbreak occurred during on

296 Using this information we correctly predicted whether any given topography within

297 intervals with digital chromoendoscopy were correctly predicted with >90 % accuracy.

298 is revealed that the sex of a donor could be correctly predicted with cross-validated accuracies of 8

299 The decoder correctly predicts, with no free parameters, the dynamic

300 eles with bystander nucleotides that BE-Hive correctly predicted would not be edited.