ライフサイエンスコーパス: clustering

1 techniques to describe the effect of habitat clustering.

2 s revealed key cell- and activation-specific clustering.

3 ch as detection of highly variable genes and clustering.

4 ing algorithms for integrative and consensus clustering.

5 cles and reduced presynaptic calcium-channel clustering.

6 atial distance and on nonspatial, asymmetric clustering.

7 e 16S ribosomal RNA gene and by hierarchical clustering.

8 ase 6 (Nek6) and Hsp72 to promote centrosome clustering.

9 s, check Mendel consistency and perform data clustering.

10 mes a function of HSET-mediated spindle pole clustering.

11 highlighting diffusion as one cause for Env clustering.

12 r through lymphocyte adhesion or Ab-mediated clustering.

13 ng action potentials; and (v) reducing spike clustering.

14 ntified factors associated with transmission clustering.

15 of eDNA and a concomitant reduction in cell clustering.

16 ld properties exhibited non-random dendritic clustering.

17 on innervation determined the sites for AChR clustering, a complete reversal of normal neuromuscular

18 A), an algorithm that substantially improves clustering accuracy.

19 Clustering affects both viral partitioning and viral gen

20 , we have made the mutation clusters and the clustering algorithm available to the public.

21 ossible chemical identity using a multistage clustering algorithm in which metabolic pathway associat

22 ated segments along the sequence, a boundary-clustering algorithm is used to refine the DCD-linker lo

23 Clustering algorithm K-means is adopted to quantify the

24 We present a clustering algorithm that achieves high accuracy across

25 We have used the spectral clustering algorithm to cluster the increasingly growing

26 rmalized adjacency matrix and use the Markov Clustering Algorithm to partition the graph while mainta

27 technologies through a bipartite-graph-based clustering algorithm, our approach turns a whole genome

28 onal studies (ADNI) using a novel multilayer clustering algorithm.

29 ing to white and gray matter by using a dual-clustering algorithm.

30 Most clustering algorithms don't properly account for ambigui

31 Recently unsupervised clustering algorithms have been proposed to identify gen

32 Despite decades of research, existing clustering algorithms have limited effectiveness in high

33 ng unsupervised dimensionality reduction and clustering algorithms, we identified molecularly distinc

34 ed with partitional, hierarchical, and fuzzy clustering algorithms.

35 Sample clustering alongside correlative assessment revealed var

36 PICK1-AP2 interactions are required for clustering AMPARs at endocytic zones in dendrites in res

37 Clustering analyses based on these outlier loci indicate

38 Based on Bayesian clustering analysis and hybridization simulations, we in

39 ion techniques combined with proximity-based clustering analysis and model simulations to investigate

40 Hierarchical clustering analysis of morpho-physiological acclimations

41 Clustering analysis of the 2D RMSD distribution leads to

42 ganized as functional networks by applying a clustering analysis on resting-state functional MRI (RSf

43 We used clustering analysis to identify putative clusters among

44 ted superresolution approaches combined with clustering analysis to study at unprecedented resolution

45 We performed clustering analysis using data from patients' hospital s

46 ndencies of these comorbidities, and network-clustering analysis was applied to derive disease subtyp

47 Unsupervised hierarchical clustering analysis was used to identify gene expression

48 subtypes, pseudo-temporal ordering of cells, clustering analysis, etc.

49 aurosporine), quantitative real-time PCR and clustering analysis, we studied gene-gene interactions i

50 n its phylogenetic distribution and sequence clustering, Anbu has been proposed as the "ancestral" fo

51 icle accumulation and acetylcholine receptor clustering and acetylcholinesterase dispersion seen in t

52 The clustering and activation of caveolin and signaling prot

53 We present a hierarchical clustering and algebraic topology based method that dete

54 Rcloud, serves a dual purpose of extracting, clustering and analyzing raw next generation sequencing

55 upon stimulation, consequently reducing BCR clustering and BCR signaling.

56 strate effectiveness of Hetero-RP in diverse clustering and classification applications.

57 by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently o

58 and oscillation begins, alternating between clustering and dispersion of particles.

59 cell receptor activation by inducing target clustering and exclusion of CD45 phosphatase from the sy

60 Gene clustering and gene trees support the idea that these ge

61 In vivo clustering and inactivation of Ire1 are not affected by

62 quality and injustice, contribute to disease clustering and interaction as well as to vulnerability.

63 lin to sites of lateral integrin alpha5beta1 clustering and is followed by tight junction formation,

64 site recording to look for evidence of local clustering and laminar consistency of linear and angular

65 e amplification are accompanied by efficient clustering and loss of E-cadherin, indicating that this

66 To optimize running time, the code uses clustering and multi-threading.

67 gle and mixed alkali compositions, metal ion clustering and percolation radically affect melt mobilit

68 spiking at high rates; and (v) reduced spike clustering and rebound potentials.

69 p learning, in combination with unsupervised clustering and reference-free classification.

70 reality and allow for fast exploration of TF clustering and regulatory dynamics.

71 Unsupervised clustering and single-cell TCR locus reconstruction iden

72 tipolar divisions, and its knockout promotes clustering and survival of cells with multiple centrosom

73 ts with gephyrin, inducing the submembranous clustering and the postsynaptic accumulation of gephyrin

74 s based on DEGs were created by hierarchical clustering and topological data analysis.

75 unsupervised segmentation learning schemes (clustering) and can be customized to employ user-designe

76 sity, perivascular CD3-positive T-lymphocyte clustering, and fibrinogen extravasation were demonstrat

77 is patients and controls showed differential clustering, and microbiota from patients with cirrhosis

78 neration, including proliferation, survival, clustering, and phagocytosis.

79 ymorphisms did not influence erythrocyte CR1 clustering, and the effects of the Knops polymorphisms o

80 asses defined by biogenesis pathway, genomic clustering, and tissue restriction, and even identified

81 Here, we describe an automated clustering approach and associated software package that

82 Here, we present a proximity-based graph clustering approach to identify TF clusters using either

83 We used a data-driven clustering approach to show that stimulation of the FPN

84 As ClusterTAD is based on a proven clustering approach, it opens a new avenue to apply a la

85 Using a data-driven clustering approach, we observed distinct temporal and d

86 tly general to replace existing unsupervised clustering approaches outside the scope of bio-medical r

87 een iCLIP replicates and single-cell RNA-seq clustering are both improved using our proposed network-

88 tine tempered autophagy, restored microglial clustering around plaques, and decreased plaque-adjacent

89 id, simple and cost-effective discrimination/clustering, as a tool to authenticate Gadidae fish speci

90 Network-based clustering associated transcripts into 22 non-overlappin

91 Most existing algorithms for integrative clustering assume that there is a shared consistent set

92 Disruption of VE-cadherin clustering at AJs (function-blocking antibody, FBA) inhi

93 to neurons and to participate in ion channel clustering at axon initial segments (AIS) and nodes of R

94 tated C2 domain all disrupted L-type channel clustering at granules and ablated fast exocytosis.

95 nce for health-care-associated infections by clustering at the hospital and country level.

96 ing of ENb to EGFR which in turn induces DR5 clustering at the plasma membrane and thereby primes tum

97 previously only been described subjectively: clustering at the temporal raphe.

98 terphase undergo a progressive polarization (clustering) at the nuclear periphery in early leptotene,

99 Hierarchical clustering based on gene expression profiles delineated

100 Finally, functional clustering based on independent resting state data revea

101 Data are then integrated using clustering-based approaches, giving hierarchical relatio

102 characterize the performance of hierarchical clustering-based methods for partitioning sequences into

103 as propagation probability, path length, and clustering behavior through the measurement of synaptic

104 uence of a cytoplasmic protein domain on the clustering behaviour.

105 as apparently consistent with differences in clustering between native E. coli receptors, with the TM

106 inner COPII coat, which contributes to their clustering between the ER and ERGIC in cells.

107 s length-dependent force generation, protein clustering by asymmetric friction, and entropic expansio

108 Significant clustering by GBS status was noted on principal coordina

109 No genotypic clustering by geographical origin or isolation source wa

110 overcome these challenges we introduce CLIC, CLustering by Inferred Co-expression.

111 Clustering by mRNA, long non-coding RNA (lncRNA), and mi

112 Clustering by mutation signature identified a high-mutat

113 eralized estimating equations to account for clustering by site was used to evaluate patient, process

114 g general linear mixed models to account for clustering by the NICU.

115 he cyclic nature of our system, we show that clustering can be induced several times by simple inject

116 hys et al. report an unexpected link between clustering capacity and cortical contractility through E

117 er alpha diversity and midrange phylogenetic clustering, characteristic of ecosystem disturbance affe

118 ficiency, clustering coefficient, normalized clustering coefficient and small-worldness values of the

119 ther with marginally significantly decreased clustering coefficient in ASD in alpha band, indicating

120 The value of the average clustering coefficient was 0.50 in the proximal colon ca

121 rength, global efficiency, local efficiency, clustering coefficient, normalized clustering coefficien

122 Clustering copy number alterations shows that most cell

123 m projection partition strategy for parallel clustering, DACE can cluster billions of sequences withi

124 0 amino acid long isoform results in vesicle clustering defects and increased synaptic depression.

125 Importantly, hierarchical clustering demonstrated an association of differential g

126 Hierarchical clustering demonstrated that bone marrow-derived mast ce

127 membrane; however, in the case of NA and M2, clustering depends upon the expression system used.

128 Most importantly, while the twofold clustering did not differ significantly between groups,

129 Unsupervised clustering displayed a phenotypic organization of CD3(+)

130 novel colloidal system that shows transient clustering driven by a chemical fuel.

131 ere we introduced an Entropy-based Consensus Clustering (ECC) method that overcomes those limitations

132 justing for important prognostic factors and clustering effects.

133 scaffolding and GRK2-CAV1 interaction, thus clustering eNOS within a complex that inhibits eNOS acti

134 A particularly common problem involves clustering entities characterized by a mixture of binary

135 pican 4 induces release of the AMPA receptor clustering factor neuronal pentraxin 1 from presynaptic

136 resent a novel approach, called perturbation clustering for data integration and disease subtyping (P

137 hat include time course expression profiles, clustering, gene ontology enrichment analysis, different

138 We find that single linkage clustering has high performance, with specificity, sensi

139 tonomous selfhood, and explaining why social clustering has occurred and been adaptive.

140 toma subtypes identified through integrative clustering have important implications for stratificatio

141 Data-driven methods such as hierarchical clustering (HC) and principal component analysis (PCA) h

142 li receptors, with the TM sequence of better-clustering high-abundance receptors being more efficient

143 alysis and 3D chemical structural similarity clustering identified unexpected FDA-approved drugs that

144 ploration of the nature and dynamics of gene clustering in plant metabolism.

145 n in endothelial cells, which impedes ICAM-1 clustering in response to HLA class I Ab and prevents ma

146 ave now identified de novo missense variants clustering in the BTB-domain-encoding region of RHOBTB2

147 le potential phosphorylation sites and their clustering in the Tau sequence.

148 n between persistent activity and functional clustering in trained recurrent neural network models em

149 n of the amygdaloid subnuclei suggests their clustering into subunits that exhibit unique functional

150 As multimerization and clustering is a prerequisite for TNFR intracellular sign

151 Centrosome clustering is a process frequently used by cancer cells

152 on the Trinity package, we propose that such clustering is a useful initial step for other assembly p

153 In addition, we show how community state-clustering is flawed when it comes to characterizing wit

154 How cell-intrinsic properties influence clustering is not entirely known.

155 Clustering is often the first step to perform in sequenc

156 rform in sequence analysis, and hierarchical clustering is one of the most commonly used approaches f

157 Integrative clustering is used to identify groups of samples by join

158 Clustering is widely used in MSI to segment anatomical f

159 At the middle clustering level, groups were separated by problem type

160 At the highest clustering level, the algorithm differentiated functiona

161 pic profiles were also evident at the lowest clustering level.

162 ata identify a hierarchy in membrane protein clustering likely being a paradigm for many cellular sel

163 is known to directly impact phosphoinositide clustering, little is known about the molecular basis fo

164 We characterized red light-induced clustering localization and adjustable diffusion of phot

165 In this article, we developed a model-based clustering method and an R function which uses DNA methy

166 tify the substructure of FAs, we developed a clustering method based on expectation maximization of a

167 A bin-based clustering method that uses statistics accumulated in bi

168 opens a new avenue to apply a large array of clustering methods developed in the machine learning fie

169 Many clustering methods have been employed to tackle this pro

170 gful interpretation than any other consensus clustering methods.

171 te functional magnetic resonance imaging and clustering methods.

172 ually curated toxin sequences using sequence clustering, network analysis, and protein domain classif

173 Unsupervised clustering of 16S rRNA gene sequences revealed three clu

174 hly concordant between hiPSCs and hESCs, and clustering of 4 cell lines within each time point demons

175 ify the patterns of comorbidity and familial clustering of a broad range of ADs in individuals with O

176 There was evidence for clustering of alemtuzumab use within transplant centers

177 l signal transmission is the positioning and clustering of AMPARs at postsynaptic sites.

178 location, allowing for trends over time and clustering of annual count anomalies by country and pool

179 Clustering of arc volcanoes in subduction zones indicate

180 f As at the Fe and S sites, as well as local clustering of arsenic.

181 e panels by downselection after hierarchical clustering of bnAb neutralization titers.

182 stem cell regulator Id4 This signature drove clustering of breast cancer cell lines and tumors into t

183 ts application to genetic regulation and the clustering of cancer samples.

184 ncipal components analysis revealed distinct clustering of cell types across samples, while different

185 Clustering of Complement Receptor 1 (CR1) in the erythro

186 is adjusting for confounding factors and the clustering of consultants revealed that the overall mort

187 x, emergency medical services response time, clustering of county, transport time to nearest PCI cent

188 random effects model was run to account for clustering of CT examinations at facilities.

189 Overall, we find significant clustering of de novo mutations in 200 genes, highlighti

190 tationally expensive to perform hierarchical clustering of extremely large sequence datasets due to i

191 ting for 38% of variation, captured temporal clustering of feeding, with high repeatability both with

192 ferentially targets lipid rafts we show that clustering of gangliosides in lipid rafts is important.

193 Principal component analysis revealed clustering of gene expression at each developmental stag

194 Distance based unsupervised clustering of gene expression data is commonly used to i

195 This leads to clustering of HCV proteins because viral particles and r

196 The clustering of illnesses in the last years of life is par

197 The clustering of individuals in large sequence datasets int

198 Clustering of infection is suggestive of host susceptibi

199 Unsupervised Markov clustering of interacting proteins identified more than

200 The clustering of intracardiac electrograms exhibiting spati

201 rvival of ER stress, but it had no effect on clustering of Ire1.

202 The clustering of KSHV plasmids provides it with an effectiv

203 The clustering of KSHV requires the viral protein, LANA1, to

204 The protective phenotype involved the clustering of macrophages around S1 segments of proximal

205 ounts and performs a modified single-linkage clustering of methylation sites into genomic regions.

206 he lamin A mutation further promotes spatial clustering of MIR335 enhancer and promoter elements alon

207 associated with congenital glaucoma revealed clustering of missense and deletion mutations in the 5-p

208 Familial clustering of MR exists in the community, supporting a g

209 reased recruitment of Munc13-4 to WPBs and a clustering of Munc13-4 at sites of WPB-plasma membrane c

210 isms, are often characterized by the spatial clustering of mutations, thereby affecting only particul

211 The study of fiber clustering of natural flocs could be useful for improvin

212 subunit-specific transcription and synaptic clustering of neuronal nAChRs, respectively.

213 as the factors regulating the expression and clustering of neuronal nicotinic acetylcholine receptors

214 windows and can perform (i) genotyping, (ii) clustering of new genomes, (iii) detect recent recombina

215 A blinded, unsupervised hierarchical clustering of participants based on global gene expressi

216 We used random intercepts to account for clustering of patients within facilities and Cox regress

217 or baseline health status and accounting for clustering of patients within sites.

218 were grouped by using unbiased hierarchical clustering of patterns of age-related leukocyte dynamics

219 However, for larvae, clustering of pesticide in the comb can lead to higher e

220 Molecular characterization and clustering of PHEOs and PGLs may help in the application

221 ulsive electrostatic forces originating from clustering of point charges on the NTD surface required

222 ated electrical field is necessary to reduce clustering of primary hydronium (H3O(+)) and product ion

223 ordinate analysis indicated a separation and clustering of samples by tissue status.

224 lled ESPRIT-Forest for parallel hierarchical clustering of sequences.

225 Through clustering of sequencing reads we can determine both num

226 plotypes in the starting population by using clustering of single nucleotide polymorphisms' trajector

227 Phylogenetic analysis found close clustering of strains from probable cases.

228 clatasvir reduced viral assembly and induced clustering of structural proteins with non-structural HC

229 ne expression in the epidermis and prominent clustering of the adjacent dermal mesenchymal cells.

230 are understood: ephrin binding triggers the clustering of the Eph receptor, fostering transphosphory

231 ermediate; (ii) reversible trimerization and clustering of the G-protein fusion loops, leading to an

232 strong concordance with previously published clustering of the mitochondrial clades based on the mtDN

233 Hierarchical clustering of the profile reliably predicted pre- and po

234 Hybrid hierarchical clustering of these six factors identified two, four, an

235 Unsupervised clustering of three intrinsic parameters that vary by ce

236 Clustering of UF and NF fractions according to ORACFPCA

237 In many applications, clustering of very large sequencing data with high effic

238 deep learning model, we performed consensus clustering on all tumor samples-leading to the discovery

239 with AF populations, with the strongest hits clustering on chromosome 4q25, close to the gene for the

240 Sl and McC polymorphisms might influence CR1 clustering on erythrocyte membranes.

241 ute the rancid fried oils using hierarchical clustering on principal component space.

242 Second, we performed hierarchical clustering on the entire dataset to investigate the unde

243 photostimulation and performed unsupervised clustering on the resulting excitatory and inhibitory co

244 ribe GECCO (Genomic Enrichment Computational Clustering Operation) to analyze somatic noncoding alter

245 does not necessarily require cooperativity, clustering, or binding site overlap.

246 We used a mixed-model analysis clustering patients according to their PD center and reg

247 Clustering patients on this basis enabled the developmen

248 ally identify genes with significant spatial clustering patterns of de novo mutations in large cohort

249 e expression profile analysis and functional clustering, PDZ domain-containing 1 (PDZK1) was revealed

250 that SIMLR is scalable and greatly enhances clustering performance while improving the visualization

251 tation data were performed with hierarchical clustering, phylogenetic analysis, and principal compone

252 removal, telomeres underwent 53BP1-dependent clustering, potentially explaining at least in part the

253 s associated with the presence of functional clustering: PPC and PFC neurons up to approximately 700

254 scular junction (NMJ) development where AChR clustering precedes innervation.

255 maximization problem to the classic K -means clustering problem, which can then be efficiently solved

256 This is a nontrivial clustering problem, with neither subgroups nor subgroup-

257 problem as an unsupervised machine learning (clustering) problem, and develop a new TAD identificatio

258 Intensified clustering promoted the initiation of synchronous bursti

259 nd present a minimal, predictive model where clustering receptors leads to their collective activatio

260 significant performance differences for most clustering-related tasks, and in the number of perceived

261 t of cluster heatmaps will perform better at clustering-related tasks.

262 The details of mechanisms underlying Env clustering remain unknown.

263 increase or decrease of the N-cadherin-EGFP clustering, respectively.

264 ccurate, robust, and biologically meaningful clustering results in both simulated data and real data

265 rincipal component analysis and hierarchical clustering, revealed different aspects of the protein-mR

266 Unbiased hierarchical clustering reveals five spatially distinct subpopulation

267 sis of principal components and hierarchical clustering sample grouping.

268 We demonstrate an automated clustering sensitivity of down to 0.1% mutant fraction a

269 Clustering should be considered when selecting seed node

270 Hierarchical clustering showed the initial magnitude and exposure tim

271 Clustering single-cell transcriptomic data identified 41

272 taneum following a similarity-based sequence clustering strategy.

273 Prior familial clustering studies have observed an increased risk of eo

274 erences in properties that were not used for clustering, such as intellectual functioning, communicat

275 Canonical correlations and hierarchical clustering techniques were applied on representative sam

276 ectal cancer network, indicating the greater clustering tendency of the proximal colon cancer network

277 Clustering the genes encoded in the individual genomes i

278 s are formed per unit dose, but due to their clustering the yields of double-strand breaks (DSB) incr

279 ic method based on a probabilistic model for clustering this type of data, and illustrate its applica

280 sampling precision, defined as the smallest clustering threshold that satisfies the third, most stri

281 widely used analysis method requires manual clustering through individual visual inspection.

282 -cell lung cancer patients, by using K-Means clustering to group patients based on esophageal radiose

283 taxonomic tree search and Dirichlet process clustering to reconstruct full-length 16S gene sequences

284 aries, suggests that cholesterol mediates M2 clustering to the neck of the budding virus to cause the

285 formulation of the multiorbital correlation clustering, together with an algorithm for obtaining tha

286 Inhibition of centrosome clustering triggers multipolar spindle formation and mit

287 VEC expression and clustering upregulated endothelial-specific genes with k

288 Hierarchical clustering using pancreatic cell lineage genes was used

289 We then apply our graph structure beyond clustering, using it to increase the accuracy of motif-b

290 ators are selected from significant genes by clustering vertexs of the mutation network.

291 K-Means clustering was able to identify three patient subgroups

292 's metabolomics profiles.First, unsupervised clustering was done with plasma metabolomics profiles fr

293 Significant spatial clustering was identified on the west side of Chicago an

294 In univariate analysis, clustering was significantly associated with subtype B c

295 K-means clustering was then used to select images from distinct

296 incipal component analysis (PCA) and k-means clustering was utilized to investigate the soil salinity

297 0 mile simulation, Cu-SSZ-13 shows Cu and Al clustering, whereas Cu-ZSM-5 is characterized by severe

298 in conformations of these helices facilitate clustering, whereas others do not.

299 In addition, we found that mossy fiber clustering, which is a common anatomical pattern, also l

300 Human ccRCC tumours clustering with cell lines display clinical and genomic