ライフサイエンスコーパス: prediction

1 nd also fits proposed future compute-system (prediction).

2 esults supports their conjoined use for risk prediction.

3 urposing, disease modeling and gene function prediction.

4 rove the accuracy of morbidity and mortality prediction.

5 for both 3- and 8-state secondary structure prediction.

6 y outperforms competing methods in phenotype prediction.

7 ghway of deep learning and protein structure prediction.

8 S adds unique predictive power in depression prediction.

9 enesis and its potential use for cancer risk prediction.

10 disrupts normal regeneration, validating our prediction.

11 riments for which the theories make distinct predictions.

12 that the ANN models led to the most accurate predictions.

13 e, but non-climatic factors complicate these predictions.

14 ystem are weighted by the reliability of its predictions.

15 , will help to build more robust and precise predictions.

16 ental trade-offs in our ability to make such predictions.

17 t isoprene hotspot is missing from bottom-up predictions.

18 have expanding impacts under global warming predictions.

19 or binding, agonist, and antagonist activity predictions.

20 ensory information with internally generated predictions.

21 om 35 studies around the world support these predictions.

22 ain, in excellent agreement with theoretical predictions.

23 and the uncertainties associated with their predictions.

24 es of osteophyte formation as influential to predictions.

25 ent Critical Assessment of Protein Structure Prediction(5) (CASP13)-a blind assessment of the state o

26 thms drive the progress in protein structure prediction, a lot remains to be studied at this merging

27 iled investigation, despite many theoretical predictions about the abundance of exotic interaction-in

28 onal work to characterize, explain, and make predictions about these pathways.

29 biomarkers with significant improvements on prediction accuracies.

30 wever, ML-based RV still faces challenges in prediction accuracy and program accessibility.

31 ess identification of 2D materials with high prediction accuracy and real-time processing capability.

32 machine-learning algorithms may increase the prediction accuracy of immunogenic peptides.

33 quares (PLS) model was constructed, giving a prediction accuracy of more than 95%.

34 ing on both genomes improves gene expression prediction accuracy on held out and variant sequences.

35 for both identification and prediction while prediction accuracy scales weakly with the number of lea

36 The best prediction accuracy was reached by combining (18)F-FDG P

37 that a larger number of qubits gives better prediction accuracy.

38 plex, highly parameterized models in age/sex prediction across increasing sample sizes.

39 trates high accuracy in EGFR mutation status prediction across patient cohorts from different institu

40 ng System (ROMS) to downscale global climate predictions across all Representative Concentration Path

41 have a pronounced effect on epidemiological predictions, affecting if, where, and to what extent FMD

42 However, current prediction algorithms have limited predictive power, in

43 ts general utility with three representative prediction algorithms including a gradient boosting mode

44 targets, yet low consensus of RNA-Seq fusion prediction algorithms makes therapeutic prioritization d

45 for image-based analysis and construction of prediction algorithms represent a new era for noninvasiv

46 ed to improve the accuracy of MHC-II binding prediction algorithms, and potentially enhance our under

47 Despite the significant progress in prediction algorithms, the fundamental predictability of

48 informative phenotypes that improve clinical prediction and clarify etiology.

49 interaction data improves the robustness of prediction and classification and advances biomarker dis

50 as repeated for a second larger set to build prediction and classification models.

51 We launch a webserver for RNA structure prediction and design corresponding to tools developed u

52 ancy of paleoclimate information for climate prediction and discuss the prospects for emerging method

53 icle, the recent applications across disease prediction and drug development in relation to the COVID

54 raction are involved with, and exploit, both prediction and its rather distant cousin, predictive cod

55 cations, such as protein-protein interaction prediction and literature-based discovery.

56 rs of neuropathic pain and might be used for prediction and monitoring of pain outcomes and stratific

57 areness and further studies mainly regarding prediction and preventive strategies in this context.

58 coding ASD risk genes was transferred to the prediction and prioritization of ASD-associated lncRNAs.

59 n Rosetta and is suitable for both structure prediction and protein design.

60 ly, DeepMSA was used for secondary structure prediction and resulted in statistically significant imp

61 -temperature operation, authentic structural prediction and short data acquisition time.

62 m experimental ground truth to gene function predictions and annotations?

63 Solid-state NMR supports these predictions and reveals pronounced spectral differences

64 Contrary to preregistered predictions and to previously published findings, MHC he

65 ic actions, to guide each other's attention, prediction, and learning processes towards salient infor

66 , current developments in diagnosis and risk prediction, and prognostic implications of AF and its co

67 evelopment of robust biomarkers for response prediction, and understanding and harnessing of escape m

68 ogy by using the revisited thermal diffusion prediction approach in inverse mode and experimental the

69 Statistical learning and probabilistic prediction are fundamental processes in auditory cogniti

70 ccording to the now canonical theory, reward predictions are represented as a single scalar quantity,

71 s, neural responses tuned away from internal predictions are suppressed.

72 the combined model dramatically improves T1D prediction at >=2 years of age over horizons up to 8 yea

73 in adults offering promise for improved risk prediction at early ages.

74 total uncertainty of 1.50% and confirms the prediction based on the chiral anomaly in quantum chromo

75 However, predictions based on different biogeochemical models are

76 vide robust estimates of the strength of the predictions beyond the placement in a ranked list, nor d

77 e properties have been an issue for accurate prediction by common theoretical probes.

78 nstrated competitive performance in PTM site predictions by other researchers.

79 The predictions by these empirical equations are validated b

80 We show that IDACombo predictions closely agree with measured drug combination

81 hese models gave significantly more accurate predictions compared to benchmarked open-access and comm

82 ence offers promising solutions for property prediction, compound design, and retrosynthetic planning

83 he management of IPNs.Methods: A Lung Cancer Prediction Convolutional Neural Network model was traine

84 Contrary to prediction, daughters born to older mothers had greater

85 The fit of our model's predictions demonstrates that males integrate assessment

86 ibration and validation sets, and a residual prediction deviation value of 3.4.

87 rthermore, natural-history data to test most predictions do not exist.

88 The accuracy of chemical structure prediction enables the development of machine-learning m

89 ormation could be down-weighted in favour of predictions encoded by the prior.

90 s not seen in the training set, resulting in predictions enriched for Ribo-seq translation signals.

91 On the basis of the mean absolute prediction error (MAE), the formulas were ranked as foll

92 It had lower root mean square prediction error (RMSPE) than when using no tool (leavin

93 bility of reward and concomitantly corrupted prediction error signalling.

94 signatures of exploration, exploitation and prediction error were unaffected.

95 e switches were most likely (strong negative prediction error), especially in subjects who obtained a

96 Specifically, prediction-error activation in the nucleus accumbens was

97 elling indicated that precision weighting of prediction errors benefits learning in health and is imp

98 only after outcome, when they encoded reward prediction errors graded by confidence, influencing subs

99 ckers, model-free phasic dopaminergic reward-prediction errors underlie learning, which renders stimu

100 on, developments regarding the estimation of prediction errors would derive in the calculation of oth

101 of neurons encoding choice outcomes, outcome prediction errors, and outcome history in their firing r

102 as 63 kJ mol(-1) in DMSO-d(6) solution (DFT prediction for a model compound in the vacuum: 90-100 kJ

103 tic: 2.81, P = 0.094), providing an accurate prediction for almost all 30-day mortality probabilities

104 ventional risk factors improved 10-year risk prediction for incident HF in a contemporary community s

105 mics to discover biomarkers and improve risk prediction for T2D.

106 d to increase its C sink capacity, while our prediction for the drier site is a net decrease in C seq

107 the codon theory continue to make important predictions for cerebellar mechanism, and we show that e

108 eshold, PLS1-DA on GC data allowed very good predictions for Chemlali variety (99% correct classifica

109 hierarchical forecasting system can generate predictions for each viral component, as well as infer a

110 direction estimation, and produces concrete predictions for future neurophysiological experiments.

111 The fellow eye no longer aided predictions for n = 5 or 6 fields (P = 0.11 and P = 0.42

112 f these neural computations lead to specific predictions for neural circuitry in the superior collicu

113 ML predictions for the methane and carbon dioxide adsorptio

114 d-to-predict proteins and that make accurate predictions for these proteins are needed.

115 Taxonomic predictions for tick-borne bacteria were exceptionally a

116 , RNA and protein composition that allow OGT prediction from genome sequence alone.

117 learning methods can be used for prospective prediction from the molecular structure without the need

118 costs remained more widely distributed than predictions from the enhanced model at all levels of fra

119 ined error thresholds, and then combines the predictions from the individual error classifiers for es

120 h ecosystem models that provide quantitative predictions from their embedded mechanistic hypotheses.

121 st few years, the field of protein structure prediction has been transformed by increasingly accurate

122 perimental studies following the theoretical predictions have confirmed the catalytic effect and the

123 Consistent with this prediction, imaging analysis show that CXCL13 binds to e

124 As a cluster expands, the predictions improve while the lead-time for vaccine deve

125 Link prediction in a complex network is a problem of fundamen

126 endent belief updating could facilitate risk prediction in bipolar disorder.

127 The accuracy of prediction in each pulmonary vein computed tomography im

128 t strong hippocampal activation to test this prediction in human neurosurgical patients implanted wit

129 between siblings is a strong test of genomic prediction in humans.

130 Potential outcomes worthy of prediction in UC were determined by surveying 202 expert

131 twist mutant embryos, where our theoretical prediction is further improved when we also account for

132 classifications, highlighting that purchase prediction is reliable even for extremely short observat

133 Based on this, a logical prediction is that differences in the integrity of the w

134 When our experience violates our predictions, it is adaptive to upregulate encoding of no

135 In agreement with the computational prediction, LNZTO demonstrates the best synthesizability

136 We created a global prediction map of groundwater arsenic exceeding 10 micro

137 stance, we design a new embedding-based link prediction method called global and local integrated dif

138 years and emerged as a potentially reliable prediction method with reasonable throughput.

139 d MapPred, a new deep learning-based contact prediction method.

140 The performance of our prediction methods indicates the potential of correlatin

141 However, current MHC-binding prediction methods lack an analysis of the major conform

142 MS will be crucial to improve variant effect prediction methods, data diversity hindered simplificati

143 roviding an opportunity to assess and refine prediction methods.

144 A periodontal prediction model (PPM) including three periodontal indic

145 sults highlighted (i) the reliability of the prediction model and (ii) the effectiveness of the antio

146 isease is important.Objectives: To develop a prediction model for estimating the probability of N0, N

147 We train the prediction model in the training set, estimate the relat

148 This HNC risk prediction model may be useful in promoting healthier be

149 Thus it is feasible to establish an accurate prediction model of outcome of SARS-CoV-2 pneumonia base

150 eoplasias in the Adnexa model system, a risk prediction model that has undergone successful prospecti

151 tudy was to compare MSI/IHC and the PREMM(5) prediction model to identify carriers of LS and non-LS p

152 Development of the prediction model was based on clinical information avail

153 x1-km grid cells from a previously validated prediction model.

154 This study investigated whether dementia prediction models developed in HICs are applicable to LM

155 cortical regions contributing heavily to the prediction models exhibited distinctive functional selec

156 Current prediction models for advanced age-related macular degen

157 Prediction models for CCS and HILIC retention time for 2

158 thesis that echolocating bats build internal prediction models from dynamic acoustic stimuli to antic

159 s in in vitro ADME tools and pharmacokinetic prediction models have helped to shift attrition rates i

160 grates acoustic snapshots over time to build prediction models of a moving auditory target's trajecto

161 In this cohort study, prediction models of acute ovarian failure risk were dev

162 We developed risk prediction models specific to the maternal critical care

163 l-based approaches for two key steps in TRMN prediction, namely somatic variant calling from exome se

164 Using subject-specific predictions, obtained uniquely from the joint model, we

165 Prediction of 10-year first CHD events (including myocar

166 Prediction of 81 biological activities associated with t

167 Timely prediction of AKI in children can allow for targeted int

168 gulum bundle may be a hallmark for the early prediction of Alzheimer's disease and a predictor of cog

169 elevance of these methods, we quantified the prediction of behavioural deficits in a prospective coho

170 When applied to de novo prediction of CDR H3 loop structures, DeepH3 achieves an

171 Another new database feature is the prediction of cell-specific miRNA targets.

172 es taken during the study contributed to the prediction of cluster assignment most accurately (84% in

173 From the prediction of curve estimation, in survivor group total

174 he improved downstream gene expression-based prediction of disease outcome.

175 Prediction of educational outcomes from polygenic scores

176 illance, diagnosis, vaccine development, and prediction of EV-D68-associated disease prevalence and p

177 (18)F-NaF PET provides powerful independent prediction of fatal or nonfatal myocardial infarction.

178 Effective prediction of future behavior with brain microstructure

179 is often quite essential, as it enables the prediction of future spatial distributions and local abu

180 O terms and isoforms, thus accomplishing the prediction of GO annotations of isoforms.

181 ltisensor Non-invasive Remote Monitoring for Prediction of Heart Failure Exacerbation) examined the p

182 ntly attracted attention after a theoretical prediction of high thermoelectric figure of merit, zT >

183 xplanation of the KLR results is that in the prediction of hinge-bending regions a long-range correla

184 lised for at least 7 days, the mean error of Prediction of Hospital Discharge Date at day 7 was 0.231

185 Accurate prediction of lncRNA-disease associations can provide a

186 lopment of a deep learning algorithm for the prediction of local gene expression from haematoxylin-an

187 identify drug mechanism of action and enable prediction of long-term cell viability from short-term t

188 of severity in ABP with clear advantages for prediction of LOS over Ranson and APACHE II.

189 We established QSAR models for prediction of MeONP-induced inflammatory potential via m

190 Moreover, prediction of methane emission by VFA indicators could b

191 diffuse excessive high signal intensity)-for prediction of motor outcomes in very preterm infants.

192 This same analysis can be used for prediction of nematode resistance and oleic-linoleic oil

193 cognition, giving insights for the potential prediction of novel substrates by combining additional a

194 tion of generalized rate expressions for the prediction of optimal binding energies of important surf

195 Meier and log-rank methods were used to test prediction of overall survival.

196 al for practical management of epidemics and prediction of pandemic risk.

197 nsula appear to be primarily involved in the prediction of physiological reactivity, whereas some reg

198 Progressing to a more mechanistic prediction of plant gas exchange is challenging because

199 One of these areas is the prediction of poor outcome, notably radiographic outcome

200 velopment and validation of an algorithm for prediction of post-traumatic stress course over 12 month

201 ating prediction uncertainty enabled precise prediction of post-treatment cartilage repair scores wit

202 Prediction of postoperative pulmonary function in lung c

203 to build and evaluate ML algorithms for the prediction of postoperative PVR using clinical data from

204 The C-statistics results for prediction of prolonged length of stay were 85 +/- 3% ac

205 vaccine and challenge viruses gave the best prediction of protection.

206 ein-protein interactions, contributes to the prediction of protein functions and facilitates protein-

207 ary measures for the diagnosis and prognosis prediction of PTSD in recently traumatized individuals.

208 f deep learning-based methods allows for the prediction of regulatory effects per variant on several

209 Therefore, accurate prediction of relative permeability using legacy models

210 e found that the GRS performed better in the prediction of renal disease in the 'later onset' compare

211 g in Cardiology Challenge 2019 on the "Early Prediction of Sepsis from Clinical Data." It consisted o

212 In summary, prediction of T2D comorbidities utilizing Danish registe

213 geometry of the bands is extracted, enabling prediction of the anomalous Hall drift, which we measure

214 ries in explicit solvent provide an accurate prediction of the experimental selectivity in the additi

215 robust algorithm for parameter inference and prediction of the hidden dynamics has been one of the co

216 rful tools for the diagnosis, prognosis, and prediction of treatment responses to improve patient str

217 works is refined with age, allowing accurate prediction of unseen individuals' brain maturity.

218 Measurements and predictions of a land-use regression model indicate mode

219 are not well understood, hampering long-term predictions of climate C-feedbacks.

220 tolerances are distributed globally, improve predictions of climate change, and mitigate effects.

221 ped in this study permits spatially explicit predictions of climate change-related population extinct

222 stroke patients (n = 101) using model-based predictions of cognitive deficits generated from the Iow

223 ebris disk offer the opportunity to test the predictions of current models of planet formation and ev

224 t events are critical steps toward improving predictions of future marine heatwaves and their impacts

225 d terrestrial biosphere models would improve predictions of global photosynthesis.

226 tial predictions to produce separate spatial predictions of migrant and resident winter habitat.

227 tic effects; (3) to estimate APPP from model predictions of NPP; (4) to test effects of simulated red

228 te experimental data and make regional-scale predictions of potential drought-induced hydraulic failu

229 ementioned improvements, the accuracy of FEP predictions of protein stability over a data set of 87 m

230 BGC-associated transporter genes can inform predictions of specialized metabolite structure and func

231 We tested core predictions of the food limitation hypothesis using a co

232 , as well as accurately produces statistical predictions of the size effects in samples of various wi

233 Model-based decisions use predictions of the specific consequences of actions, but

234 erns of variability across genomes; accurate predictions of their effects are, therefore, important f

235 In line with predictions of this Sync model, midfrontal theta power w

236 ental results disagree with some theoretical predictions of when they are extended to a population di

237 provement when used for downstream structure prediction on families with the longest length sequences

238 ity is used as a simple descriptor to make a prediction on whether a given aryl fluoride substrate fa

239 tion and calculation of Best Linear Unbiased Predictions or Best Linear Unbiased Estimates.

240 echanists, including motion tracking, motion prediction, parameter optimization, model fitting, elect

241 omatic alterations data for cancer prognosis prediction, pathway-level models are more interpretable,

242 wledge from these two domains and to enhance prediction performance for both tasks.

243 According to evaluations of candidate gene prediction performance tested under four different seman

244 Prediction performance was evaluated internally (in the

245 ic predictors of host phenotype by comparing prediction performances and biological interpretation ac

246 stantial interobserver variability in expert predictions, performing better than five out of six expe

247 Surprisingly, we find that for all ten predictions, plants and animals show similar patterns.

248 of networks respectively, and compared their prediction power using three classification algorithms a

249 holesterol goals), additional tests for risk prediction, primary and secondary prevention, laboratory

250 In this model, secondary structure prediction programs are used to calculate diversity indi

251 in presbycusis was provided by pathogenicity prediction programs, documented haploinsufficiency, thre

252 tal results and supported by the theoretical predictions, provides a way to study the effect of defec

253 ble, the observed human PK are compared with predictions, providing an opportunity to assess and refi

254 ors, four machine learning models have close prediction results for the phenotype measured in Area Un

255 cuss the current state of breast cancer risk prediction, risk-stratified prevention and early detecti

256 ediction schemes and outcome studies using a prediction scheme for treatment decisions, the present e

257 ven in the absence of fully established risk prediction schemes and outcome studies using a predictio

258 nic stroke), the refinement of AF and stroke prediction schemes through comprehensive digital phenoty

259 sion models, which were then translated into prediction scores.

260 vitro DNA-binding experiments and structural prediction show that CTM provides an important domain fo

261 in structures on the results of binding-site prediction, so the dataset contains a minimum of two lig

262 transformed by increasingly accurate contact prediction software.

263 hasize the need for improved diagnostic/risk prediction strategies to guide antibiotic prescribing fo

264 est practices and recommendations related to prediction study design, conduct, and reporting.

265 The standard approaches used for TFBS prediction, such as position weight matrices (PWMs) and

266 ls in general and species-specific 6 mA site prediction, suggesting it can provide a useful resource

267 s reward-driven vigour, contradictory to the prediction that increased tonic dopamine amplifies rewar

268 We then tested the prediction that NQO1 induction by pharmacological activa

269 ng this framework results in reliable growth predictions that are important for assessing individual

270 which enables the computation of integrated predictions that may improve future learning.

271 Here we provide evidence supporting the key predictions that prestige-biased social learning is used

272 We reexamine this prediction through a theoretical treatment of the interp

273 ristics are insufficient for making accurate predictions; thus, a proteome-wide understanding of phas

274 an approach for using EHR data and clinical prediction to generate quantitative measures from binary

275 lored features which were most important for predictions to better understand movement imitation diff

276 mics (MD) simulations initiated from Rosetta predictions to gain insights on the interplay of amino a

277 We then integrated these spatial predictions to produce separate spatial predictions of m

278 rforming model that provided the most robust predictions to project trajectories of alien species num

279 down-weighting retrieval of erroneous memory predictions to promote an updated representation of the

280 his study was to develop and validate a risk prediction tool for trauma-induced coagulopathy (TIC), t

281 lar Rosetta fragment-based protein structure prediction tool.

282 Most T cell epitope prediction tools are based on machine learning algorithm

283 ntegrated structural databases and fusion of prediction tools toward protein disorder characterizatio

284 del in handling missing data and calculating prediction uncertainty enabled precise prediction of pos

285 0% for each method, with successful swarming prediction up to 30 days prior to the event.

286 Finally, we perform survival prediction using a hybrid method of deep learning and ma

287 O:E ratios, suggesting high accuracy in risk prediction using current models.

288 CCS prediction using machine learning (ML) has recently show

289 error of 26%, although uncertainty in model prediction was substantial (CV = 28%).

290 xtending these dynamical features to disease prediction, we find that attractor topography of nutrien

291 Confirming our predictions, we found that inputs from both eyes, studie

292 The current criteria used for miRNA target prediction were inferred on a limited number of experime

293 e strengths and limitations of the consensus predictions were discussed with example chemicals; then,

294 AI predictions were evaluated using 10-fold cross-validatio

295 In test set 1, segmentation-free RNFL predictions were highly correlated with conventional RNF

296 gle crystals and thin films, and theoretical predictions were made using molecular dynamics simulatio

297 Predictions were tested psychophysically in human observ

298 twork predicts more accurate sub-compartment predictions when SCI-determined sub-compartments are use

299 of 90% or better for both identification and prediction while prediction accuracy scales weakly with

300 ntially reduces the time required to perform prediction with minimal resource requirements allowing f