ライフサイエンスコーパス: ensemble

1 essible memory cells in a macroscopic atomic ensemble.

2 ki coupling reaction to achieve the required ensemble.

3 representation of Abeta10-40 conformational ensemble.

4 36 that is dominant in the Abeta42 reference ensemble.

5 lision cross sections of each conformational ensemble.

6 the distribution of leaf nodes of the model ensemble.

7 nd to the GO sheets to form a GO/aptamer-QDs ensemble.

8 r secondary structure throughout the dynamic ensemble.

9 structural modeling of the kinase's solution ensemble.

10 urther improve the quality of the determined ensemble.

11 prior for the structure of the excited state ensemble.

12 g (BMA) to optimize the integration of model ensemble.

13 and temperature) affect the denatured-state ensemble.

14 ant optical excitations to spin-polarize the ensemble.

15 n other fractions as well as the unseparated ensemble.

16 ably enhancing beta-structure in the monomer ensemble.

17 decrease in H2O2 reduction by the AhpF-AhpC ensemble.

18 stent and complete picture of the underlying ensembles.

19 can be used to determine RNA conformational ensembles.

20 is achieved by complex multipartite enhancer ensembles.

21 understand how coordination emerges in human ensembles.

22 the steady-state fluorescence spectra of FCP ensembles.

23 time, is observed throughout frontostriatal ensembles.

24 ic heterogeneity usually masked in molecular ensembles.

25 rties specifically on cue-activated neuronal ensembles.

26 ucture on information coding in the neuronal ensembles.

27 ields) were ranked accurately by three-model ensembles across crop species and field sites.

28 asticity was selectively expressed in the MC ensembles activated by the stud male, consistent with fo

29 known about specific changes within neuronal ensembles activated during the recall of drug-environmen

30 elerometer and video data, we found that SPN ensembles active during specific actions were spatially

31 two-photon calcium imaging revealed that M2 ensemble activity also showed earlier activity onset and

32 gated the spatiotemporal organization of SPN ensemble activity in mice during self-paced, natural mov

33 ctive state is robust to changes in stimulus ensemble and adaptive state.

34 Using a combination of ensemble and single-molecule spectroscopy, we have scrut

35 sites results in a fuzzy chaperone-substrate ensemble and suggests a mechanism for Hsp70 function whe

36 t pathways using PL measurements at both the ensemble and the single particle level.

37 to promote the separation of male and female ensembles and to induce an attack response 24 h later.

38 y, we demonstrate that our model Hamiltonian ensemble approach is able to provide a reliable fully fi

39 This ensemble approach is compatible with many reconstruction

40 s based on resampling techniques and a hyper-ensemble approach that outperforms state-of-the-art meth

41 full, calibrated models was required for an ensemble approach to keep variability below that of comm

42 ge impact on potato may be improved using an ensemble approach.

43 of drug response prediction errors based on ensemble approaches with various combinations of genetic

44 The elastic properties of such an ensemble are determined by the average number of myosin

45 ergy landscape changes on the conformational ensemble are particularly challenging to visualize for l

46 Because conformational ensembles are an inevitable feature of proteins, this is

47 Hierarchical ensembles are efficient computational methods that guara

48 s, due to systematic model biases, the CMIP5 ensemble as a whole underestimates the chance of future

49 tory modulates OFC activity, we recorded OFC ensembles as rats performed spatial discriminations that

50 This study uses large-ensemble atmospheric simulations with prescribed ocean s

51 udies, the x-ray techniques only provided an ensemble average of the structural information from all

52 P waves recorded with carotid catheters were ensemble averaged relative to the R-peaks of the electro

53 ccounts for both noise in the data and their ensemble-averaged nature.

54 However, previous studies have reported ensemble-averaged results that cannot distinguish the im

55 e classical analogue of Rabi oscillations in ensemble-averaged spins of a ferromagnet.

56 l surface sites, information that is lost in ensemble-averaged techniques.

57 e states because they typically only provide ensemble averages rather than information about individu

58 le forcing solution investigations to report ensemble averages.

59 measuring platform, while noise reduction by ensemble averaging simultaneously lowers the background

60 By removing ensemble averaging, single-molecule methods provide uniq

61 the heterogeneity idea in the commonly used ensemble based predictive model of Random Forests, we pr

62 ve a lower bound for the number of entangled ensembles based on the contrast of the interference and

63 se residue interaction graphs with provable, ensemble-based algorithms to reap the benefits of sparse

64 Here, we nurture the idea of ensemble-based learning by combining bagging and boostin

65 omerase render them difficult to study using ensemble biochemical and structural techniques.

66 Here, using single-molecule fluorescence and ensemble biophysical techniques, and a wide range of pH

67 ates directional inhibition between local PC ensembles but may also shape communication hierarchies b

68 e increased photoluminescence from divacancy ensembles by up to three orders of magnitude using near-

69 We validate these structural ensembles by using ChIP-Seq tracks alone to predict Hi-C

70 CNEs are organized into functional ensembles called genomic regulatory blocks-dense cluster

71 nsemble, there is still debate over how this ensemble changes with environmental conditions.

72 In ensembles, Cin8 motors were able to produce single-motor

73 show that the XSI-based model of the TAR RNA ensemble closely resembles an independent model derived

74 A molecular ensemble comprising more than 20 molecules is involved i

75 INTERPRETATION: Our model ensemble confirmed established and identified novel pred

76 Distinct optical chirality relevant to the ensemble conformation is demonstrated from the assembled

77 antum memory based on a mesoscopic neodymium ensemble coupled to a photonic crystal cavity.

78 single-photon level-a technique to suppress ensemble decoherence due to inhomogeneous broadening.

79 observed that the coordination level of the ensemble depends on group homogeneity, as well as on the

80 curve in which the collective growth of the ensemble depends on the number of local populations incl

81 rewarded trials separated goal switches, OFC ensembles developed stable and anticorrelated population

82 g possibilities for the design of disordered ensembles, disorder-to-order transitions, or design for

83 ate but not to mount or attack conspecifics, ensemble divergence did not occur.

84 lor centers enables the probing of nanoscale ensembles down to approximately 30 nuclear spins in atom

85 reduced prediction errors of the full model ensemble E-median for crop grain yields (from 36% at sta

86 strate entanglement between over two hundred ensembles, each containing a billion atoms.

87 onary approach known as the Multidimensional Ensemble Empirical Mode Decomposition (MEEMD) method, to

88 s vital for long-term memory, but how neural ensembles encode associative memories is unknown.

89 oughout the experiments, the strength of the ensemble-encoded CS-US association predicted the level o

90 We find that ensemble encoding of the value of the first offer includ

91 The nanoparticle ensemble exhibited selectivity towards Arg by showing di

92 al conditions and a 50-member climate change ensemble experiment, consisting of historical hindcasts

93 Ensemble experiments have shown that the fluorescence of

94 tion that is unavailable through traditional ensemble experiments.

95 ependent medial prefrontal cortex-projecting ensemble extinguished aversive responses to enable flexi

96 We refer to this new approach as Ensemble Flux Balance Analysis (EnsembleFBA).

97 nerating polypeptide backbone conformational ensembles for intrinsically disordered peptides and prot

98 n types and the subsequent 3D conformational ensembles for the even chromosomes.

99 ework is then used to generate retrospective ensemble forecasts of historical WNV outbreaks in Long I

100 Hippocampal place cell ensembles form a cognitive map of space during exposure

101 At stage 1, ensembles formed by the three lowest prediction model er

102 nsic excitability in Fos-expressing neuronal ensembles (FosGFP(+)) that were activated during food se

103 learning model called gradient boosting tree ensemble (GDBT) was applied to the samples that allowed

104 te optimized prion conformations from larger ensembles generated in the species of origin.

105 heir scenario dependence using three sets of ensemble global climate model simulations.

106 nalogous to polymerization in three aspects: ensemble growth statistics following models for step-gro

107 The highest lifetime, lowest free-energy ensemble identified consisted of native conformations ad

108 rose cue exposure recruited a more excitable ensemble in the nucleus accumbens, but not orbitofrontal

109 e activated receptor selects a subset of the ensemble in which multiple substates are apparently reta

110 D1 and D2 family receptors, and DMS neuronal ensembles in "incubated" methamphetamine seeking, using

111 study assessed the excitability of neuronal ensembles in the nucleus accumbens core and shell (NAc(c

112 in concert to shape and synchronize neuronal ensembles in the PFC, these alterations could contribute

113 itical role of dorsomedial striatum neuronal ensembles in this new form of incubation of drug craving

114 eruginosa and six Streptococci, we show that ensembles increase the quality of predictions without dr

115 Here we review evidence that ensemble integration may result from LTP but also from c

116 sibility of artificially imprinting neuronal ensembles into awake, behaving animals and of later reca

117 Each subtype ensemble is also tuned for rotation.

118 The spin ensemble is coupled to the resonator through its orbital

119 remains unclear how the Hsp70 conformational ensemble is populated at each point of the allosteric cy

120 deep cooling of the mesoscopic nuclear spin ensemble is used to achieve long qubit coherence.

121 The functional optimization of neural ensembles is central to human higher cognitive functions

122 c excitability of appetitive memory-encoding ensembles is regulated differentially across brain areas

123 The relation with Gibbs ensembles is studied and understood.

124 ts such as reduced order modelling (ROM) and ensemble kinetic simulation (EKS).

125 The optimally integrated ensemble LAI changes are significantly closer to the obs

126 of diabetes parameter regression based on an ensemble learning algorithm named double-Class AdaBoost.

127 useful in DNA-binding residue prediction and ensemble learning can be used to address the data imbala

128 Random forests are an ensemble learning method that provides predictions with

129 In the computational experiments, two ensemble learning methods outperform benchmark branchpoi

130 Third, we propose two ensemble learning schemes which integrate different feat

131 features and different classifiers to build ensemble learning systems for the branchpoint prediction

132 physiological responses at both the neuronal ensemble level as observed by electroolfactogram and the

133 m urea unfolding intermediate of V75D at the ensemble level using solution NMR and small-angle x-ray

134 this kind of serial dependence occurs at the ensemble level, where local elements are already merged

135 nism, and kinetic equations solution for the ensemble long-time propagation (based on information col

136 The predictor was developed using an ensemble machine learning approach with up-sampling of t

137 TMLE implementation, particularly the use of ensembled machine learning algorithms.

138 , via the formation of supramolecular chiral ensembles made out of small chiral adsorbates, and by ad

139 Here we exploit the recently developed multi-ensemble Markov model framework to compute full protein-

140 Unlike previous studies that used multimodel ensemble mean (MME), we used the Bayesian model averagin

141 The multi-model ensemble mean (MMEM) shows that the response of ecosyste

142 studies based on fine-resolution models, an ensemble mean of CMIP5 models projects an increase in TC

143 with a 3% yield, a phenomenon unobserved in ensemble measurements under analogous experimental condi

144 been hindered by inhomogeneous broadening in ensemble measurements, as well as imperfect control over

145 r voluntary abstinence and that DMS neuronal ensembles mediate this incubation.

146 ion from Biomarkers Associated to Structural Ensembles (MEGABASE), on odd-numbered chromosomes, we pr

147 Across CMIP5 ensemble members, March Barents Sea SIE trends have litt

148 loning and merging steps, as in the weighted ensemble method.

149 experimental results show that hierarchical ensemble methods are able to predict novel associations

150 characterize different oligomeric species by ensemble methods, especially the dimer that cannot be re

151 f Disease analytic tools, the Cause of Death Ensemble model and DisMod-MR 2.1, were used to produce e

152 Ensemble modeling (EM) was developed to circumnavigate t

153 Small angle X-ray scattering and ensemble modeling yielded models of the PHn-PHc fragment

154 We report reactive ensemble Monte Carlo simulations for the CO2 methanation

155 In addition, we find that ON and OFF ensemble neural activities differ in their ability to re

156 these with alterations in less activated non-ensemble neurons (FosGFP(-)).

157 This ensemble non-Gaussian behavior is caused by a combinatio

158 tions between states within a conformational ensemble occur over a broad spectrum of amplitude and ti

159 al Chromatin Model (MiChroM)] to generate an ensemble of 3D chromosome conformations at a resolution

160 port an atomistic model of the excited state ensemble of a stabilized mutant of an extensively studie

161 ovide evidence that general functions of the ensemble of amacrine cells across types are critical for

162 y, therefore we computationally generated an ensemble of apoCaM-Ng13-49 structures by matching the ch

163 ionylation on the equilibrium conformational ensemble of BAK1 using all-atom molecular dynamics simul

164 provided by paired-end reads, as well as the ensemble of both.

165 chromatin types determine the 3D structural ensemble of chromosomes through a process similar to pha

166 for which no ChIP-seq data exists, onto our ensemble of classifiers and show that our cross-sample T

167 Using a large ensemble of climate models, our results confirm that glo

168 An open conformation emerges from an ensemble of closed conformations in a highly Na(+)-depen

169 available, and we generated a representative ensemble of cognate and non-cognate complexes.

170 be used, for example, to compare a simulated ensemble of conformations to NMR diffusion measurements.

171 and we successfully propagate this into the ensemble of CQDs.

172 nhancing kainate potency and diminishing the ensemble of desensitized states.

173 ues, we present a methodology called SELDOM (enSEmbLe of Dynamic lOgic-based Models), which builds an

174 ges in GPLLJ frequency using an eight member ensemble of dynamically-downscaled climate simulations f

175 We identified an ensemble of effective model parameters using measurement

176 given network; here we characterize a broad ensemble of empirical networks in terms of the fraction

177 Understanding of the conformational ensemble of flexible polyelectrolytes, such as single-st

178 have shown that GPCRs exist temporally in an ensemble of interchanging conformations.

179 r the energy landscape, thereby changing the ensemble of likely low-energy conformations.

180 optimization enabling the construction of an ensemble of local models that captures fluctuations as t

181 Dynamic lOgic-based Models), which builds an ensemble of logic-based dynamic models, trains them to e

182 disease and healthy controls to construct an ensemble of models to predict the annual rate of change

183 By analysing an ensemble of models we find that, within the next 15 year

184 ore limited to an average measurement of the ensemble of molecular interactions.

185 We conclude that AfGcHK functions as an ensemble of molecules sampling at least two conformation

186 Here, we use a dense ensemble of neodymium rare-earth ions strongly coupled t

187 Here we show that an ensemble of nine crop models reproduces the observed ave

188 ed with net biome productivity (NBP) from an ensemble of nine terrestrial ecosystem models, to attrib

189 Examining the ensemble of particle displacements reveals a Laplace dis

190 In nanodiscs, however, an ensemble of pH-dependent conformational substates is obs

191 pectation and variance of the dynamics of an ensemble of populations.

192 These findings also suggest that the ensemble of prefusion structures presents many potential

193 terminal domain is unfolded and comprises an ensemble of random conformers, without any detectable re

194 RACIPE generates an ensemble of random kinetic models corresponding to a fix

195 tatistical mechanical analysis for the whole ensemble of sgRNA-target complex conformations, we ident

196 In this study, we evaluate an ensemble of six different downscaled climate models and

197 An ensemble of spinners exhibits chaotic dynamics due to se

198 In this study, we describe the equilibrium ensemble of structures of Slo2.2, a neuronal Na(+)-activ

199 uctures of a protein, our method uncovers an ensemble of structures that fully accounts for the obser

200 tionary conservation and other factors in an ensemble of TFCT-specific classifiers.

201 which may alter the native-state structural ensemble of the molecule, leading to aggregation-prone i

202 losteric communication within the structural ensemble of the protein.

203 An ensemble of the two reached F of 0.46.

204 molecules but even better agreement with an ensemble of this molecule and two of the partially exten

205 dicted potential invadable areas based on an ensemble of three ecological niche modelling methods, an

206 An ensemble of transient meltwater simulations shows that A

207 tworks, we imaged the activity of a complete ensemble of wing control muscles in intact, flying flies

208 q, which predicts molecular dynamics-derived ensembles of a more exhaustive set of DNA shape features

209 d comparative analysis of the conformational ensembles of amino-truncated Abeta10-40 peptide produced

210 icroscope, we tracked the Ca(2+) dynamics of ensembles of amygdalar neurons during fear learning and

211 ics simulations to determine the equilibrium ensembles of an insulin molecule under amyloidogenic con

212 odor identity can accurately be decoded from ensembles of co-active neurons that are distributed acro

213 Two ensembles of CO2 were observed in the SILM, one in the I

214 molecular dynamics simulations to determine ensembles of conformations corresponding to the denature

215 Proteins are dynamic entities and populate ensembles of conformations.

216 entials in terms of similarity or generating ensembles of electrostatic potential files for a library

217 The conformational ensembles of IDPs are encoded by their amino acid sequen

218 iological partners and thus exist as dynamic ensembles of interconverting conformers, often highly so

219 ces generated within microtubule networks by ensembles of key proteins.

220 se stimuli, we recorded neural activity from ensembles of LGN neurons in cats across early developmen

221 lve subtle differences in the conformational ensembles of nucleic acids, on the order of 1-2 A.

222 we must understand how the brain represents ensembles of objects at many levels of perceptual analys

223 tly been used to characterize conformational ensembles of proteins in the microcrystalline states, it

224 scopy, we have measured here the forces that ensembles of purified budding yeast kinesin-5 Cin8 produ

225 At the single unit level, we found that ensembles of putative dopamine and non-dopamine VTA neur

226 Here we present high-resolution structural ensembles of ribosomes with cognate or near-cognate amin

227 r characterizing the solution conformational ensembles of RNAs and RNA-protein complexes under divers

228 Ensembles of solid-state optical emitters enable broadba

229 The solution structure and dynamic ensembles of the duplexes reveals that in both cases, m1

230 are the computationally generated structural ensembles of the IDP amyloid-beta42 (Abeta42) to an alte

231 Thus, empirically, the MANOVA ensemble offers a universal description of the spectra o

232 experiments can be used to prepare small NP ensembles on a UME (i.e., UME-NPEs).

233 ing ColN as a flexible system, namely by the ensemble optimization method, which enables a distributi

234 s corresponded to the similarity between SPN ensemble patterns, irrespective of movement speed.

235 we investigate the functional usefulness of ensemble perception and its efficiency, and we consider

236 Ensemble perception refers to the visual system's abilit

237 For this task, SELDOM's ensemble prediction is not only consistently better than

238 ombines their individual simulations into an ensemble prediction.

239 confirmed as differentially expressed by the ensemble predictions obtained in a regression model.

240 An amygdala-projecting ensemble promoted aversive learning, while an independen

241 Optimization of the equilibrium ensemble properties of the target test tubes implements

242 mPFC and CA1 ensembles recorded simultaneously predicted goal choices

243 MENT The present study used behavioral data, ensemble recordings from medial premotor cortex (MPC) in

244 of statistical physics, we analyzed how the ensemble relaxes to a stationary distribution and establ

245 Yet depiction of protein structural ensembles remains difficult.

246 Place cell ensembles reorganize to support learning but must also m

247 How PFC ensembles represent shifts in behavior in response to ch

248 Sensory information is translated into ensemble representations by various populations of proje

249 The dynamics of ensemble representations formed by distinct channels of

250 This discoordination causes place cell ensemble representations of a familiar space to cease re

251 n enormous amount of visual information into ensemble representations, such as perceiving a forest in

252 gh both populations showed reorganization of ensemble representations.

253 r architecture permits stable and replicable ensemble responses to diverse sensory stimuli under vari

254 The infrared spectrum of the droplet ensemble reveals several signatures of polar, water tetr

255 suboptimal conformational space based on the ensemble's partition function.

256 ehaving animals and of later recalling those ensembles selectively by stimulating individual cells.

257 a high-resolution global climate model, the ensemble showed a more uniform change throughout the Nor

258 ng to ongoing cortical oscillations, and SPN ensembles showed higher levels of rhythmic correlated fi

259 creased intrinsic excitability of Fos(-) non-ensembles.SIGNIFICANCE STATEMENT Prefrontal cortex activ

260 These forecasts are generated using ensemble simulations depicting local influenza transmiss

261 owever, the uncertainties of (reduced) model ensemble simulations have not been assessed systematical

262 te that a single hybrid model of the TAR RNA ensemble simultaneously fits both the XSI and NMR-RDC da

263 rise from extrinsic effects such as residual ensemble size distributions, impurities, or solvent-rela

264 In combination with integrated mutagenesis, ensemble-solution kinetics, and molecular dynamics simul

265 Although sleep-associated ensemble spike activity has been investigated, identifyi

266 remarkable collective order of other animal ensembles, such as fish and birds [2], the kinematic pro

267 exhibits a relatively compact conformational ensemble that binds AP-1, whereas CLK2-PAGE4 is more exp

268 tein and drug binding motifs in the HERV RNA ensemble that do not occur in minimum free energy or cen

269 sparsely distributed neurons called neuronal ensembles that are activated selectively by reward-predi

270 overconverge to a single solution; it gives ensembles that could further evolve under selection.

271 excitability of PLC Fos-expressing neuronal ensembles that play a role in food seeking but decreased

272 Applied among a crowd of Gentle Boost ensembles, the ability of the two suggested algorithms t

273 a protein is a heterogeneous conformational ensemble, there is still debate over how this ensemble c

274 Here, Li et al. show how to map a spin ensemble to a spring model so analytic pulses can be des

275 gle axis in this space, allowing a face cell ensemble to encode the location of any face in the space

276 map generation methods with optimized model ensembles to address the inherent challenges of segmenti

277 and highlight the importance of multi-model ensembles to estimate the uncertainty surrounding the fu

278 Then, we cluster these diverse ensembles to identify the most diverse partition functio

279 The potential of using process-based model ensembles to predict jointly productivity and N2 O emiss

280 ransport relies on myosin Va molecular motor ensembles to travel along the cell's three-dimensional (

281 Previous ensemble transient kinetic studies have estimated the av

282 or terminates) for an approximately 10 motor ensemble transporting a 350 nm lipid-bound cargo that en

283 slatory optic flow fields, creating a neural ensemble tuned for a specific direction of motion throug

284 ces among models to CO2 drive divergence and ensemble uncertainty in relative change in NPP over the

285 Densely packed Cu NP ensembles underwent structural transformation during ele

286 The SigSeeker peak-calling ensemble uses multiple tools to identify peaks, and with

287 rtex (OFC) and nucleus accumbens (NAc) shell ensembles using wild-type and Fos-GFP mice, which expres

288 Using median model ensemble values, yield increased on average 6% per 100-p

289 iking feature of the resulting excited state ensemble was an unstructured N-terminus stabilized by no

290 , a highly robust supramolecular H-bonded 1D ensemble was used to order the appended crown ethers in

291 aging observations and a large climate model ensemble, we quantify uncertainty in the influence of gl

292 reliability of neuronal coactivity patterns (ensembles), which was not a simple consequence of altere

293 lative probabilities of conformations in the ensemble, which in turn, depend on the exact amino acid

294 selective groups of neurons, called neuronal ensembles, which are emergent building blocks of neural

295 at long times are captured by a statistical ensemble with nonzero thermodynamic entropy, which is th

296 Herein, silver nanoparticles ensemble with Zn(II) complex of alpha-liopoic acid conju

297 in a crystal that contains many large atomic ensembles with distinct resonance frequencies.

298 vation of topographically ordered functional ensembles with moderate local mixing.

299 ory by coordinating the activity of neuronal ensembles within the medial temporal lobe (MTL).

300 e in vitro from a native-like conformational ensemble without the need for a transition across the ma