ライフサイエンスコーパス: dimensionality

1 dimensional approaches due to 'the curse of dimensionality'.

2 e number of other variables (high shattering dimensionality).

3 criptor class that typically has the highest dimensionality.

4 r phenotypes in vitro because of their three-dimensionality.

5 nced data, especially in the context of high-dimensionality.

6 the advantages conferred by high shattering dimensionality.

7 lect a biologically appropriate latent space dimensionality.

8 tice: changes in composition, structure, and dimensionality.

9 Principal Component Analysis to reduce data dimensionality.

10 his is at the core of the so called curse of dimensionality.

11 termolecular spin-spin coupling with limited dimensionality.

12 ical, unresolved issue, given graphene's two-dimensionality.

13 lems such as the activity cliff and curse of dimensionality.

14 he Fourier space with greatly reduced design dimensionality.

15 g regarding the importance of the structural dimensionality.

16 d is amenable to problems of extremely large dimensionality.

17 er-by generic hydrodynamic forces-to reduced dimensionality.

18 cause of the very large data volume and high dimensionality.

19 e interplay between crystalline symmetry and dimensionality.

20 thout weight sharing) can avoid the curse of dimensionality.

21 tial discretization that leads to a curse of dimensionality.

22 esearchers fit a single algorithm and latent dimensionality.

23 to obtain new molecules with enhanced three-dimensionality.

24 dentified in models trained with more latent dimensionalities.

25 ained using an intermediate number of latent dimensionalities.

26 component analysis (PCA) to reduce spectral dimensionality (1203 features) and support vector machin

27 e need to understand the nature of the shape dimensionality (1D vs 2D vs 3D) of cell-scaffold interac

28 ng and kidney cancer TCGA datasets with high dimensionality, again showing clinically significant res

29 ist of a mixture of domains having different dimensionality, allowing energy funneling from lower-dim

30 on and analysis of TMD crystals encompassing dimensionalities and morphologies beyond 2D.

31 models across a large range of latent space dimensionalities and observe various performance differe

32 r cell-type-discriminative markers to reduce dimensionality and achieve informative cell typing resul

33 le methods including estimation of intrinsic dimensionality and assessment of reconstruction of out-o

34 eoretical guarantees that avoid the curse of dimensionality and by testing them on a variety of proto

35 examine the effect of electrical coupling on dimensionality and chaotic dynamics, we first determined

36 materials, the crystal structure defines the dimensionality and connectivity of interstitial sites, t

37 The work elucidates the key role of dimensionality and dual topological phases in selecting

38 ures shared by different instances, reducing dimensionality and enabling generalization in novel situ

39 the model, which could be used to reduce the dimensionality and improve predictive power.

40 al networks is challenging due to their high dimensionality and inherent anisotropy.

41 orchestrated reduction of manifolds' radius, dimensionality and inter-manifold correlations.

42 However, due to high dimensionality and low study power, current studies usua

43 sensitive to initial conditions due to high dimensionality and nonconvexity of the NMF paradigm.

44 Here, we study the dimensionality and orientation of TDMs in CdSe quantum r

45 However, inclusion of network data increases dimensionality and poses additional challenges for commo

46 l energy surface of the K2Rb complex in full dimensionality and report numerically-exact quantum-mech

47 d visualization, requiring methods to reduce dimensionality and represent the data in a compact way.

48 number, spacing and affinity, as well as the dimensionality and rigidity of scaffold presentation on

49 However, the high dimensionality and sparsity of scATAC-seq data often com

50 consider replicas of the system to tune the dimensionality and take the limit as the number of repli

51 ted from the population's low-level features-dimensionality and temporal smoothness-alone.

52 g to which electrical coupling regulates the dimensionality and the complexity in the inferior olive

53 ling the direct relation between the graphs' dimensionality and the rate of propagation of the viral

54 Here, we computed the levels of synchrony, dimensionality, and chaos of the inferior olive code by

55 s and the interconnected nature of topology, dimensionality, and symmetry in electronic systems.

56 spatial variation is transient regardless of dimensionality, and that structured initial conditions l

57 l frustration, quantum fluctuations, and low dimensionality are the most often evoked material's char

58 lustrates the wide-ranging potential of high-dimensionality artificial-nose based sensing systems for

59 of the spectroscopic information differs in dimensionality as well.

60 d theoretical formulation bring to light the dimensionality, as a hidden constraint on carrier dynami

61 , including the role of hydrogen bonding and dimensionality, as well as the optical and magnetic prop

62 rgue that entorhinal grid cells encode a low-dimensionality basis set for the predictive representati

63 us experiments have augmented the real-space dimensionality by one additional physical synthetic dime

64 nal topological insulator phenomena to lower dimensionality by utilizing a pumping parameter (either

65 This curse of dimensionality can be partially mitigated by using the t

66 ng compressed features across algorithms and dimensionalities captures the most pathway-associated re

67 , such as the ribbons of COF-76, into higher dimensionality COFs, paves the way to covalent framework

68 gically meaningful interpretation and modest dimensionality compared with voxelwise approaches.

69 of longitudinal metagenomics data, i.e. high-dimensionality, dependence among samples and zero-inflat

70 also enables exploration of new and exciting dimensionality-driven magnetic phenomena.

71 The lack of dimensionality effect on the transition temperature defi

72 equisites for molecular additives to achieve dimensionality engineering, defect passivation, molecula

73 pression models across multiple latent space dimensionalities enhances biological representations.

74 s, with increasing structural complexity and dimensionality, for a measles-like infectious disease.

75 The curse of dimensionality has long been a hurdle in the analysis of

76 er, whether other perovskites with different dimensionalities have the same effect on efficiency and

77 are required to translate the increased data dimensionality, heterogeneity and complexity into patien

78 nsurate block layer that yields enhanced two-dimensionality, high electronic quality, and clean-limit

79 that is capable of (i) identifying multiple dimensionalities in a dataset, and (ii) providing accura

80 nswers may provide insights into the role of dimensionality in high-temperature superconductivity.

81 One of them is the reduction of effective dimensionality in many systems with orbital degrees of f

82 This study probes the role of dimensionality in modulating the aggregation behavior of

83 Our results highlight the role of structure dimensionality in stabilizing the oxygen lattice in reve

84 n data points is frustrated by the "curse of dimensionality" in high dimensions.

85 As dataset size and dimensionality increase, linear chemometric techniques l

86 mmetries via quasiperiodic ordering with low dimensionality into a material system promises the emerg

87 Second, the dimensionality is a better indicator than average correl

88 it synthetic control of their morphology and dimensionality is a major challenge.

89 The lattice dimensionality is established by circuit connections, an

90 tracting stable phenotypic features, fitting-dimensionality is reduced and reliable prognostic models

91 , we address the fundamental question of how dimensionality is related to connectivity, in both auton

92 romagnetic CrN films with strain and reduced dimensionality is reported.

93 ein, the coupling between l-OR and structure dimensionality is studied.

94 ark states, they need to span a space with a dimensionality larger than one, so different orthogonal

95 ink connects microbes to genes using reduced-dimensionality LDA topics.

96 Compliance and dimensionality mechanosensing, the processes by which ce

97 When trained with different latent dimensionalities, models learn strongly associated and g

98 he nanocluster's size in controlling the NCF dimensionality, modulating the optical properties, and i

99 tures of low-dimensional TMD crystals (e.g., dimensionality, morphology, and phase) will afford acces

100 , 2, 3 ... infinity) and reversibly tune the dimensionality (n) by modulating the strength and number

101 ges inherent in 'omics' data, including high-dimensionality, noise, and timing differences in express

102 capture the time-encoding properties and the dimensionality observed in the data.

103 sed methods have been proposed to reduce the dimensionality of 1 D 1H NMR datasets, including statist

104 EC materials and the well-proven fractional dimensionality of 2.5 for ferroelectric domain walls.

105 The larger dimensionality of 3D MR Spirometry advantageously allows

106 ing of an over-saturated model with the high-dimensionality of a genomic dataset.

107 The dimensionality of a network's collective activity is of

108 Our system can be used to increase the dimensionality of a photonic lattice and induce long-ran

109 dology allows to dynamically probe the local dimensionality of a transportation network and identify

110 from bulk solids arise from constraining the dimensionality of an inorganic structure(1-3).

111 link prediction, and discover the intrinsic dimensionality of brain networks.

112 Continued expansion in the size and dimensionality of cardiovascular imaging databases is dr

113 the optimal representation of the intrinsic dimensionality of data and show it is a noninteger.

114 The high-dimensionality of data generated by flow cytometry usual

115 nt a forecasting algorithm that exploits the dimensionality of data in a nonparametric autoregressive

116 ry data analysis is made complex by the high dimensionality of data.

117 nature, the implicit value of increasing the dimensionality of datasets is shown using cell lysates f

118 and the product ions combined with the high dimensionality of DIA data sets hinder accurate feature

119 s and show how to incrementally increase the dimensionality of entanglement.

120 First, the dimensionality of global activity patterns can be strong

121 However, because of the ultra high-dimensionality of GWAS data, such analysis is challengin

122 However, others have stressed that the high dimensionality of human technologies makes them very dif

123 h synchrony and was inversely related to the dimensionality of inferior olive firing dynamics, as mea

124 and behaviour (foraging strategy and spatial dimensionality of interactions) interactively affect fea

125 ounds, that the cerebellum must regulate the dimensionality of its neuronal activity during motor lea

126 However, the high-dimensionality of microbiome data, often in the order of

127 We investigated the dimensionality of midfrontal theta by applying advanced

128 We found that the dimensionality of neural population activity was higher

129 ng the values of novel objects increases the dimensionality of neural representations in dlPFC.

130 e changes in patterns of activity affect the dimensionality of neural responses and information about

131 t opportunity for genetic research, the high dimensionality of omic data and complex relationships am

132 imal learns to discriminate the odorants the dimensionality of PRP decreases.

133 Consistent with hypotheses about the dimensionality of psychosis, our results provide novel e

134 As the dimensionality of SCO is reduced, the lattice constant e

135 r challenges is to model the temporality and dimensionality of sequential influenza strains and to in

136 teristics over time that can help reduce the dimensionality of SES data by enabling the assignment of

137 nt aspects of stability reflecting the multi-dimensionality of stability.

138 ine the power exponent, which represents the dimensionality of surface diffusion, and results to be d

139 We extended the quantity and dimensionality of TFBSshape, from mostly in vitro to in

140 interactions between nanoelements lowers the dimensionality of the ASI from 2-D to 1-D.

141 ajority of significant QTL and to reduce the dimensionality of the association model.

142 properties of Bi(2)O(2)Se while reducing the dimensionality of the bonding network connecting the Bi(

143 mponents analysis was employed to reduce the dimensionality of the data and a grid of neural network

144 ectral descriptors, effectively reducing the dimensionality of the data set.

145 The high-dimensionality of the data with few biological replicate

146 lenging though, due to the sparsity and high dimensionality of the data.

147 der parameter, and also because of the three-dimensionality of the electronic structure.

148 Here we analysed the dimensionality of the encoding of natural images by larg

149 correlations grow, due to the relatively low dimensionality of the exploratory variation in compariso

150 An autoencoder is then used to reduce the dimensionality of the feature vector to obtain the optim

151 The dimensionality of the field has expanded with the apprec

152 linear nature of sensory processing and high dimensionality of the input.

153 In addition, by significantly reducing the dimensionality of the marker profile, DeepMicro accelera

154 d comparable to the experimental values when dimensionality of the materials is taken into account an

155 The low dimensionality of the model enables us to derive these c

156 rom neural data and computing the cumulative dimensionality of the neural trajectory over time.

157 We find that the effective dimensionality of the non-interacting lattice component

158 =Ca, Sr, Ba) and Mn(2+) demonstrate that the dimensionality of the obtained material is controlled by

159 e been limited studies investigating how the dimensionality of the physical and electrical microenvir

160 The benefit of our algorithm grows with the dimensionality of the problem and the complexity of the

161 Last, there was a decrease in dimensionality of the representational space after train

162 exemplar learning as well as the underlying dimensionality of the representational space.

163 We argue that the dimensionality of the space available for population cod

164 s work opens the possibility to increase the dimensionality of the state-space used for encoding info

165 In addition, the dimensionality of the synthetic water channels also impo

166 ncipal component analysis in order to reduce dimensionality of the variability across multiple data g

167 The SWNT templates control the dimensionality of the wires, allowing precise control of

168 etworks are difficult to predict due to high dimensionality of their interactive space.

169 Because of the high dimensionality of these datasets, multivariate ordinatio

170 t substantially transforms the structure and dimensionality of TMD crystals without lithography.

171 The 'dimensionality' of the mechanical milieu under which exp

172 e the role of carrier diffusion and material dimensionality on the carrier recombination kinetics and

173 There is no single best latent dimensionality or compression algorithm for analyzing ge

174 skites, however, is characterized by reduced dimensionality perovskites, emphasizing the two-dimensio

175 The curse of dimensionality plagues models of reinforcement learning

176 Dimensionality plays an important role in the charge tra

177 tiferromagnetic domains and its non-integral dimensionality point to a hitherto-unobserved magnetic f

178 The plethora of benefits owed to reduced dimensionality prompted exploration of expanding non-lay

179 This is because dimensionality provides a compact measure of how coordin

180 chemical components, crystal structure, and dimensionality, providing a unique set of building block

181 imensional and nonlinear relationships, with dimensionality ranging from 1 to 1000.

182 moderately complex, varying key features of dimensionality, reaction type, reaction speed, crowding,

183 Dimensionality reduction (DR) methods have been develope

184 s, combined effect analysis, and multifactor dimensionality reduction (MDR) analysis.

185 clinical variables (Model 1), and after PCA dimensionality reduction (Model 2).

186 ure clustering, selection, normalization and dimensionality reduction algorithms, and five commonly u

187 urvival analysis, similar gene detection and dimensionality reduction analysis.

188 Using unsupervised dimensionality reduction and clustering algorithms, we i

189 Even simple downstream analyses, such as dimensionality reduction and clustering, require days of

190 propose an ensemble method for simultaneous dimensionality reduction and feature gene extraction (ED

191 efficient population coding scheme based on dimensionality reduction and sparsity constraints.

192 study, we develop a pipeline that integrates dimensionality reduction and statistical modeling to gra

193 tein conformational search, efficient robust dimensionality reduction and topological analysis via pe

194 Support Vector Machines (SVM), coupled with dimensionality reduction and variable selection algorith

195 d projection (UMAP) is applied for nonlinear dimensionality reduction and visualization of mass spect

196 ochemical profiles, we apply a bidirectional dimensionality reduction approach taking into account bo

197 The new methodology is compared to competing dimensionality reduction approaches through a simulation

198 ubject groups using k-means clustering after dimensionality reduction by t-neighbor stochastic neighb

199 Proper dimensionality reduction can allow for effective noise r

200 Here, we test this dimensionality reduction hypothesis by relating a data-d

201 tunately, despite the critical importance of dimensionality reduction in scRNA-seq analysis and the v

202 Dimensionality reduction in the training set established

203 Dimensionality reduction is an essential first step in d

204 Dimensionality reduction is an indispensable analytic co

205 utational efficiency and easy visualization, dimensionality reduction is necessary to capture gene ex

206 Dimensionality reduction is often used to visualize comp

207 Dimensionality reduction is widely used in the visualiza

208 We demonstrate that the choice of dimensionality reduction method can significantly influe

209 ut, and uses the state-of-the-art non-linear dimensionality reduction method t-Distributed Stochastic

210 onomic count data, and another commonly used dimensionality reduction method, Principal Component Ana

211 Here we apply dimensionality reduction methods (PCA, t-SNE, PCA-t-SNE,

212 We use two dimensionality reduction methods as well, robust Princip

213 e the computational scalability of different dimensionality reduction methods by recording their comp

214 However, existing dimensionality reduction methods could not be directly a

215 in scRNA-seq analysis and the vast number of dimensionality reduction methods developed for scRNA-seq

216 We evaluate the performance of different dimensionality reduction methods for neighborhood preser

217 we provide important guidelines for choosing dimensionality reduction methods for scRNA-seq data anal

218 ive evaluation of a variety of commonly used dimensionality reduction methods for scRNA-seq studies.

219 d to evaluate the effectiveness of different dimensionality reduction methods in scRNA-seq.

220 Specifically, we compare 18 different dimensionality reduction methods on 30 publicly availabl

221 We also investigated the effect of dimensionality reduction methods on the performance of t

222 omes project data, we examine how non-linear dimensionality reduction methods such as t-distributed s

223 Nonlinear dimensionality reduction methods such as Uniform Manifol

224 We introduce several dimensionality reduction methods to visualize in 2- and

225 , we use normalized edit distance to enhance dimensionality reduction methods, including Isomap and L

226 Using dimensionality reduction methods, we find that V1-V2 int

227 data has motivated continuous development of dimensionality reduction methods.

228 Three multiview dimensionality reduction methods: multiview t-distribute

229 Principal component analysis (PCA) dimensionality reduction obtained a 2-dimensional repres

230 of visualization and is well-suited for the dimensionality reduction of large (>100 000 pixels) MSI

231 pathways enable efficient decorrelation and dimensionality reduction of photoreceptor signals while

232 that functional groups of spines defined by dimensionality reduction of receptive field properties e

233 Dimensionality reduction of RNA expression profiles via

234 able Model (GPLVM) is a popular approach for dimensionality reduction of single-cell data and has bee

235 We present a novel framework, ivis, for dimensionality reduction of single-cell expression data.

236 methods suggested for feature extraction and dimensionality reduction of such data.

237 Here, we examine not only the dimensionality reduction of this mapping but also its te

238 Dimensionality reduction reveals fine-scale population s

239 for the RPM algorithm, which is a nonlinear dimensionality reduction technique designed to produce a

240 Using a statistical nonlinear dimensionality reduction technique on single-trial ensem

241 Feature selection is one such high-dimensionality reduction technique that helps to maximiz

242 classes of procedures, among them classical dimensionality reduction techniques and others incorpora

243 cartography, particle image velocimetry, and dimensionality reduction techniques reveal that these os

244 Here, we explore the application of various dimensionality reduction techniques that have been used

245 Different from existing dimensionality reduction techniques, the proposed method

246 using machine learning algorithms to perform dimensionality reduction to capture eigengenome informat

247 d signal processing feature extraction, (ii) dimensionality reduction to differentiate dynamical path

248 classification, unsupervised clustering and dimensionality reduction to learn cancer-relevant data r

249 We describe a dimensionality reduction tool, compositional tensor fact

250 Machine learning (ML) provides powerful dimensionality reduction tools.

251 , a statistical method for visualization and dimensionality reduction using a tropical polytope with

252 Dimensionality reduction using the polynomial terms alon

253 images of 1800 microstructures, followed by dimensionality reduction via principal component analysi

254 vercome these difficulties, we propose DR-A (Dimensionality Reduction with Adversarial variational au

255 We find evidence of goal-directed dimensionality reduction within human ventromedial PFC d

256 SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full inte

257 workflow: feature calculation and selection, dimensionality reduction, and data processing.

258 discordance as the effects of localization, dimensionality reduction, and irreversible enzymatic rea

259 of neural coding, computational methods for dimensionality reduction, and sensory-perceptual perform

260 code covering transformation, normalization, dimensionality reduction, clustering, and pseudotime ana

261 igh-dimensional statistical ideas, including dimensionality reduction, clustering, subsampling, and r

262 ariate analysis that simultaneously provides dimensionality reduction, feature extraction and multi-c

263 ction, clustering, normalization, selection, dimensionality reduction, predictor construction, best d

264 Using an evolutionary algorithm and dimensionality reduction, we discovered metaparameters,

265 riven modelling approach using probabilistic dimensionality reduction, we investigate covariation acr

266 ut irrelevant information, a process akin to dimensionality reduction.

267 broadly applicable data-driven algorithm for dimensionality reduction.

268 ategy to quantify gene relevance and improve dimensionality reduction.

269 ons with low-dimensional functions including dimensionality reduction.

270 data-driven approach to fulfill the task of dimensionality reduction.

271 of using multiview methods of clustering and dimensionality reduction; however, none of these methods

272 ilt on a concept intentionally orthogonal to dimensionality-reduction methods.

273 on was accompanied by an overall increase in dimensionality (reflecting less information redundancy)

274 distinction in carrier dynamics in different dimensionality regimes informs new design rules for opti

275 Such dimensionality regulation is possible via modulation of

276 In a historic context, however, low dimensionality represents the exception which stands in

277 Our results establish the minimum dimensionality required for avian functional traits to p

278 precursors offer a unique combination of low dimensionality, structural rigidity, and distinct interi

279 y which the brain may untangle the 'curse of dimensionality': synchronization of confidence represent

280 etwork responses of either greater or lesser dimensionality than the stimulus.

281 magnetic atoms unravels a hidden transverse dimensionality that can be exploited to engineer energy

282 played by ion channel function and the lower dimensionality that captures physiological function.

283 Secondary outcomes included examination dimensionality (that is, the number of factors measured)

284 ntext of cell signaling, we show that system dimensionality - the shape of the extracellular medium a

285 Owing to their restricted dimensionality, the nominally one-dimensional MoS(2) nan

286 al population analyses often reduce the data dimensionality to focus on relevant activity patterns.

287 Model data were fit to assess questionnaire dimensionality, to estimate item information, and to sco

288 um wavefunctions and various factors such as dimensionality, topology, Coulomb interactions and symme

289 into some important topics, including trait dimensionality, trait spectra (including the leaf econom

290 ld indicate a quantum cutting due to the low dimensionality.Understanding the confinement and transpo

291 By taking advantage of dimensionality, we show that AR-RBFN overcomes the short

292 profiles can suffer from the problem of high-dimensionality, where making useful inferences can be di

293 Metasurfaces are metamaterials of reduced dimensionality which have opened up new avenues for flat

294 are best captured in models trained at lower dimensionalities, while more subtle signals such as path

295 techniques to handle data sparsity and high dimensionality, while evaluating potential biomarkers in

296 Plasmons depend strongly on dimensionality: while plasmons in three-dimensional syst

297 imaging microscopy spectra of unprecedented dimensionality will catalyze advances in systems biology

298 The increase in dimensionality with learning in object blocks was relate

299 The reduction in connective dimensionality with retention of electronic functionalit

300 The resolution and dimensionality with which biologists can characterize ce