ライフサイエンスコーパス: individual cell

1 bryos from measurements of up to millions of individual cells.

2 mation of metabolic and functional states in individual cells.

3 ed AFMOTs to trap and deform freely floating individual cells.

4 s of large copy-number aberrations (CNAs) in individual cells.

5 ationary phase, which arises only in 3-5% of individual cells.

6 ns to analyze the transcriptomic profiles of individual cells.

7 uality, which allows for the segmentation of individual cells.

8 ntification of further, discrete proteins in individual cells.

9 of a large number of genome-wide features in individual cells.

10 technique for measuring the transcriptome of individual cells.

11 enome sequencing of hundreds to thousands of individual cells.

12 eterogeneous residency of cohesin at CARs in individual cells.

13 -seq (scRNA-seq) profiles gene expression of individual cells.

14 parse signal across hundreds or thousands of individual cells.

15 their expression state by sequencing 38,285 individual cells.

16 ts or particles with a final goal to analyze individual cells.

17 essibility correlate with gene expression in individual cells.

18 t single guide RNA (sgRNA) identification in individual cells.

19 gregation of single hcn plasmid molecules in individual cells.

20 sion is associated with increased fitness of individual cells.

21 igh variability of chromatin architecture in individual cells.

22 full characterization of transcriptomes from individual cells.

23 ne expression and epigenetic variation among individual cells.

24 thod to estimate and remove contamination in individual cells.

25 only provide a transcriptional 'snapshot' of individual cells.

26 Microbes are often thought of as individual cells.

27 patial, proteomic and lineage information in individual cells.

28 e catalogues detailing the transcriptomes of individual cells.

29 s in the whole mass range as fingerprints of individual cells.

30 mage processing to identify and characterize individual cells.

31 ues we show that they rarely co-occur within individual cells.

32 esearchers to assay the epigenetic states of individual cells.

33 de data and data reflecting fork movement in individual cells.

34 ingful probabilities of spatial position for individual cells.

35 emphasizing the heterogeneous nature of the individual cells.

36 uring the exact status of DNA replication in individual cells.

37 standing fundamental molecular mechanisms in individual cells.

38 of the epigenetic landscape of thousands of individual cells.

39 eq) to determine the transcriptomes of 4,391 individual cells.

40 nhancers to individual stemness genes within individual cells.

41 tanding of gene expression and regulation in individual cells.

42 -Seq (scRNA-Seq) profiles gene expression of individual cells.

43 ot intended to resolve heterogeneity between individual cells.

44 ell types from the transcriptional output of individual cells.

45 ework for the investigation of expression in individual cells.

46 the whole transcriptome of a large number of individual cells.

47 nformation from otherwise static profiles of individual cells.

48 ta at resolutions comparable to the sizes of individual cells.

49 ng genome-wide gene expression levels within individual cells.

50 ovide insight into signaling pathways within individual cells.

51 into cellular heterogeneity and dynamics of individual cells.

52 level reflects heterogeneous dynamics among individual cells.

53 vered via the determination of metals in the individual cells.

54 nalysis for clustering the transcriptomes of individual cells.

55 HV replication with diverse kinetics between individual cells.

56 ing analysis of splicing heterogeneity among individual cells.

57 lly altering the abundance of metabolites in individual cells.

58 patterns via the control of transcription in individual cells.

59 P22 expression and trafficking efficiency in individual cells.

60 insights into the dynamical processes within individual cells.

61 ecause of variable boundary positions across individual cells.

62 contain zero counts for many transcripts in individual cells.

63 gh-resolution mapping of chromatin states in individual cells.

64 ables studying gene expression programs from individual cells.

65 state and accessible chromatin variation in individual cells.

66 sion phenomenon emerges from the dynamics of individual cells.

67 s and precise control of heterogeneity among individual cells.

68 13 and IRE1alpha was not altered in affected individuals' cells.

69 ins difficult to comprehensively genotype an individual cell(1).

70 y predict the nanoparticle dose delivered to individual cells across a population.

71 lize quality metrics and read alignments for individual cells across multiple samples or runs are sti

72 we performed single-cell RNA-seq on >50,000 individual cells across three tissues in young and old m

73 pable of measuring, in parallel, hundreds of individual cells' adhesion forces with a resolution at t

74 n principles by categorising the response of individual cells against a time-varying signal.

75 ynamic information of subcellular mechanics, individual cell allostasis is observed to occur through

76 rogates genome-wide chromatin interaction in individual cells, allowing us to gain insights into 3D g

77 rapid development for molecular analysis of individual cells among heterogeneous populations.

78 escribe a mass cytometric, multidimensional, individual cell analysis of differentiating myoblasts th

79 Most of the 6986 individual cells analyzed with nanometer-scale secondary

80 echnology that can assess the function of an individual cell and cell-to-cell variability at the sing

81 junctions, namely between the cytosol of an individual cell and its extracellular environment.

82 applying controlled mechanical stress on an individual cell and simultaneously reporting dynamic inf

83 of CRISPR-Cas as a system that protects the individual cell and supports growing evidence of abortiv

84 eractions and their localization at both the individual cell and whole-tissue scales with single inte

85 and can be a source of heterogeneity within individual cells and across populations.

86 contribute to functional differences between individual cells and animals.

87 ession associated with reduced expression in individual cells and decreased number of cells expressin

88 ident macrophages rapidly sense the death of individual cells and extend membrane processes that sequ

89 riptional heterogeneity at the resolution of individual cells and have an increasing impact on biomed

90 hers to study transcriptomic activity within individual cells and identify inherent cell types in the

91 us to examine the function and morphology of individual cells and identify two classes of pretectal n

92 ting in decreased overall IRF4 expression in individual cells and increased heterogeneity within the

93 actions between mechanochemical signaling in individual cells and interactions with cell-cell junctio

94 s is typically done by isolating hundreds of individual cells and measuring expression levels of mult

95 ae It is unknown how spatial trajectories of individual cells and the collective motions of many cell

96 cell populations, which enabled us to track individual cells and their clonal outgrowth during tumor

97 on of multiple distinct sgRNA sequences from individual cells and thus allows pooled single-cell CRIS

98 Identifying the FSHD transcriptome in individual cells and unraveling the cascade of events le

99 ng enzyme activities in lysates derived from individual cells and will contribute to the understandin

100 e and dynamic phenotypic characterization of individual cells and, in particular, analysis of secrete

101 e a rate constant of a catalytic reaction in individual cells and, thus, facilitate accurate size det

102 s at the levels of intracellular structures, individual cells, and cell groups.

103 The structure of TADs is variable between individual cells, and inter-TAD associations are common.

104 ion of morphological regions of interest and individual cells, and we apply this pipeline to the rege

105 out of forces across cells could compromise individual cell apical geometry and thereby organ functi

106 Individual cells are encapsulated with antibody-conjugat

107 tive measurements of metabolic activities of individual cells are essential to understanding question

108 Using flow cytometry, individual cells are first sorted into a well plate cont

109 se to only a handful of such binding events, individual cells are unlikely to experience the average

110 cs, genomics, and proteomics at the level of individual cells, are ideally suited to studying these p

111 ection methods can be useful for identifying individual cells as well as their phenotype in one step.

112 A cell concentrations across a population of individual cells, as well as variabilities in drug metab

113 ing sequential eviction and intercalation of individual cells away from the serosa margin.

114 this information can be used to classify an individual cell based on its transcriptional profile.

115 principle, we tagged, isolated, and expanded individual cells based on three biologically relevant vi

116 We emphasize the importance of analyzing individual cells because some cells are apoptotic, in S-

117 c system and V-cup array was used to capture individual cells before optical measurement of light sca

118 eta-catenin modulator delta-catenin controls individual cell behavior to promote cancer.

119 et been fully realized for investigations of individual cell behaviors and phenotypic changes in dens

120 While these individual cell behaviors have been extensively studied,

121 arrangement of cells without specifying the individual cell behaviors needed to achieve it.

122 rough locally specifying and then summing up individual cell behaviors, like oriented cell division.

123 In the intestinal tract, individual cells build thousands of microvilli, which pa

124 LDI) MS can measure the chemical contents of individual cells but spectra are difficult to correlate

125 r the individual cells, gene measurements at individual cells can be used to study several different

126 ution, thousands to hundreds of thousands of individual cells can now be analyzed in an individual ex

127 Whether individual cells can tailor their behavior to the limite

128 investigations have revealed a multitude of individual cell-cell interactions important for this sel

129 e immune system is the prolific expansion of individual cell clones that encounter their cognate anti

130 d and applied for the extraction of RNA from individual cell clusters in the central nervous system o

131 etry, where stochastic behaviors of multiple individual cells collectively result in a balance betwee

132 the refractive index and cell morphology of individual cells concomitant with enhanced photon activi

133 oducibility was observed down to the area of individual cell contacts.

134 The health status of individual cells could be effectively predicted using an

135 We find that migration of individual cells depends on the feedback between mechani

136 Individual cells detach from cohesive ensembles during d

137 Matrix dynamics influence how individual cells develop into complex multicellular tiss

138 tem cells and their progeny, and to quantify individual cell divisions from time-lapse movies of expl

139 ral stress response sigma factor sigma(B) in individual cells during biofilm development.

140 ge of the CHD transcription factor, TBX5, in individual cells during cardiomyocyte differentiation fr

141 The dynamic behaviour of ERK activity in individual cells during this transition is unclear.

142 mplification subsequently took 13 to 14 h in individual cells during which their compartments occupie

143 ng transmission identifies full infection of individual cells effectively from a single viral entry.

144 A hollow patch pipette is attached to individual cells, enabling the recording of electrical a

145 s to systematically quantify the behavior of individual cells every 2 minutes during Phallusia mammil

146 breast and colorectal cancers, we show that individual cells evolve into tumors or aspects of tumors

147 mics model of the ePBR, which predicted that individual cells experienced rapid fluctuations (~6 s) b

148 e bead-based technologies uniquely barcoding individual cells, facing practical challenges for precio

149 tion with a linked Flp/frt reporter to track individual cell fates.

150 attern is caused by the intrinsic avidity of individual cells for FDG, the density of viable cells in

151 a moderate level of cross-reactivity primes individual cells for optimal proliferative responses fol

152 an unprecedented level of resolution across individual cells for studying cell heterogeneity and gen

153 ecome a powerful tool to study the genome of individual cells for the detection of mosaic mutations.

154 tumor spheroids reflect the contractility of individual cells for up to 1 hr after seeding, while col

155 Through RNA-sequencing of 100,987 individual cells from 7 primary, 2 recurrent, and 2 lung

156 However, individual cells from fibroblast cell lines have heterog

157 d the study of thousands or even millions of individual cells from malignant tumours at the single-ce

158 cing characterized the transcriptomes of 544 individual cells from mouse embryonic kidneys.

159 Catcher automatically separates and isolates individual cells from multi-cell images; Mito Catcher us

160 se control of action-potential generation of individual cells from neuronal ensembles.

161 s that average the gene expressions over the individual cells, gene measurements at individual cells

162 -lapse microscopy-based method that observes individual cells growing into microcolonies.

163 tissue is particularly well-defined because individual cell growth is essentially the mechanical yie

164 A-seq (scRNA-seq) experiments, the number of individual cells has increased exponentially, and the se

165 llow high-throughput expression profiling of individual cells, have significantly advanced our abilit

166 sequencing (scRNA-seq) provides details for individual cells; however, crucial spatial information i

167 measuring gene expression from thousands of individual cells identified the different cell types in

168 <0.05% of the total protein content from individual cells in a 16-cell Xenopus laevis (frog) embr

169 cellular states might affect the response of individual cells in a clonal population to cisplatin, a

170 s have allowed measuring gene expression for individual cells in a population, thus opening up the po

171 que for characterizing the transcriptomes of individual cells in a sample.

172 es the gene expression state of thousands of individual cells in a single experiment, offering advant

173 ) collect mRNA counts from up to one million individual cells in a single experiment; this enables hi

174 Individual cells in a solution display variable uptake o

175 a metabolic modeling approach that can track individual cells in both space and time, track the diffu

176 Individual cells in clonal populations often respond dif

177 acing provides key insights into the fate of individual cells in complex organisms.

178 dentifying the number, location, and type of individual cells in images.

179 for quantifying and analyzing properties of individual cells in large fluorescent microscopy dataset

180 ies enable genome sequencing of thousands of individual cells in parallel, but with extremely low seq

181 A spatial metric for individual cells in scRNA-seq data is first established

182 a long-term cultivation approach of patient-individual cells in the presence of viruses.

183 , but little is known about the responses of individual cells in this area in humans.

184 e repeated visualization of fine features of individual cells in three-dimensional space over several

185 e quantification of protein synthesis within individual cells in vivo.

186 phogenesis requires accurate segmentation of individual cells in volumetric images of growing organs.

187 functional diversity in ECs at the level of individual cells; indeed, fresh EC isolates from lung an

188 a high variability along the contact of one individual cell, indicating a local regulation of endoth

189 P concentration reflected the severity of an individual cell injury, allowing to discriminate between

190 Individual cells integrated global motion over ~200 ms,

191 Super-resolution imaging of individual cells is required for better understanding of

192 Multiplexed RNA sequencing in individual cells is transforming basic and clinical life

193 ines which process dominates during aging of individual cells is unknown.

194 f spatiotemporal coordination of ZGA between individual cells is unknown.

195 Individual cell level data also confirm that the metacyc

196 Studies on KSHV gene regulation at the individual cell level would allow us to better understan

197 ature of KSHV replication/gene expression at individual cell levels.

198 Our approach allows identification of individual cells making transition between all cell stat

199 erences in the transcriptome and proteome of individual cells may create cellular hierarchies, which,

200 Direct physical interactions among individual cells mediate large-scale architectural biofi

201 as an excellent SHG-indicator of changes of individual cell membrane and periplasm properties of liv

202 Because individual cell migration is an early step in breast can

203 Individual cell migration requires front-to-back polarit

204 epithelium and work in concert to coordinate individual cell movements for collective migration.

205 rocessing algorithm, DiFC allows counting of individual cells moving in arterial or venous directions

206 een developed to map axes of variation among individual cells, no analogous approaches exist for iden

207 ttering, we measured the dry mass content of individual cell nuclei within spheroids.

208 ces on a single microparticle embedded in an individual cell of an embryo.

209 Individual cells of cyanobacteria or algae are supplied

210 MSI of individual cells (of a known cell type) affords a unique

211 Trajectories of individual cells on the order of several seconds to few

212 of regulation network for identity genes in individual cell or tissue types.

213 individual cis-regulatory elements (CREs) in individual cells or rare cell subpopulations.

214 d via gradual repression of transcription in individual cells over several cell cycles, and that the

215 infection, both among host cells and within individual cells over time.

216 By analyzing thousands of individual cells per patient tumor, we identified the mo

217 Tracking of hundreds of individual cells (per condition) over a 9-h time series

218 aims to identify all progeny arising from an individual cell, placing them within a lineage hierarchy

219 metries, we find that specific properties of individual cells (polarizability; contractility) influen

220 method for elucidating the contributions of individual cell populations to embryonic development and

221 riptomic and epigenomic profiles in the same individual cells provide an unprecedented opportunity to

222 llows the measurement of transcriptomes from individual cells providing new insights into complex bio

223 in C. elegans is determined independently by individual cells rather than via cell-to-cell communicat

224 e from Ramon y Cajal states that neurons are individual cells, rejecting the process of cell-cell fus

225 Individual cells rely on conserved defenses to prevent a

226 l (3D) genome organization in the underlying individual cells remains largely obscured because the co

227 phase of reductive palinotomy, the volume of individual cells remains the same through development.

228 d environments on the trajectory of aging in individual cells remains unclear.

229 e demonstrate that tumorigenicity depends on individual cells residing in this E/M hybrid state and c

230 Tracking of individual cells revealed two distinct fates: one set of

231 ill lacking fundamental understanding of how individual cells sense and respond to diverse stress con

232 However, individual cells' signaling responses to pro-inflammator

233 us to visualize allelic Gata3 expression in individual cells simply by flow cytometry.

234 Individual cell sizes are variable and adaptable, but wh

235 trometer platforms representing thousands of individual cell spectra that were collected and used to

236 We identified 25 nodes (individual cell subtype-epitope-ligand combinations) sig

237 related with DUSP6 and DUSP10 transcripts in individual cells, suggesting that ERK activity is negati

238 namics of NF-kappaB nuclear translocation in individual cells, suggesting the integration of NF-kappa

239 ction of multicellular tissue architectures, individual cells, synaptic spines and rare cell-cell int

240 capture multiple mechanistic ER endpoints in individual cells that are affected by EDCs, we previousl

241 a database of morphological features for 630 individual cells that encode 0, 1 or 2 alleles of the mi

242 r hormone and targeted therapies and tracked individual cells that express markers of cancer stem cel

243 For each individual cell, the maximal ER Ca(2+) uptake rate and t

244 that accounts for the size and shape of the individual cells, the fraction of ECM, and its stiffness

245 At the level of individual cells, the role of mechanical forces is well

246 nce of transcriptional reinduction memory in individual cells through multiple divisions.

247 evertheless is repeatedly lost and gained in individual cells throughout development.

248 d electrochemical currents to energy gain by individual cells, thus overlooking the potentially compl

249 in vivo somatic transgenesis that allows for individual cells to be genetically manipulated, tracked,

250 ological levels of organization ranging from individual cells to cell ensembles and whole organisms.

251 f highly fluorescent biological samples from individual cells to environmental samples.

252 Non-genetic factors can cause individual cells to fluctuate substantially in gene expr

253 r forces are generated and maintained within individual cells to induce tissue curvature.

254 r work highlights the remarkable capacity of individual cells to process multiple input signals and s

255 membrane composition and its changes within individual cells to specific biochemical functions or st

256 The determination of individual cell trajectories through a high-dimensional

257 e cell-state landscape, the determination of individual cell trajectories through that space can be c

258 expression and co-expression patterns of an individual cell type.

259 lk tissue analysis do not resolve changes in individual cell-type proportion or gene expression.

260 ution, we here explored the heterogeneity of individual cell types and dissected their transitions an

261 e limited our ability to study the origin of individual cell types and stem cell units.

262 proximity, has prevented characterization of individual cell types and/or their developmental progres

263 ies that provide greater resolution into how individual cell types are affected by disease and the co

264 We next generated all iPSC-LBs by incubating individual cell types in ultra-low attachment micro-dimp

265 Characterization of individual cell types is fundamental to the study of mul

266 is secreted by many tissues, but the role of individual cell types is unclear.

267 t differential SECISBP2 protein stability in individual cell types may dictate clinical phenotypes to

268 nhance understanding of the contributions of individual cell types to the physiological states of the

269 to PBMCs, and several pathways identified in individual cell types were absent in PBMCs.

270 visual system using genetic lines to access individual cell types, the TAPIN-seq method to measure t

271 etween diagnoses, especially at the level of individual cell types.

272 hich obscures gene expression changes within individual cell types.

273 regulatory programs enabling regeneration of individual cell types.

274 ples often reflect changes in proportions of individual cell types.

275 erences in FcgammaRIII glycosylation between individuals, cell types, subcellular locations, and path

276 n and differentially methylated cytosines in individual cell-types (DMCTs) for a range of different t

277 the simultaneous transcriptomic profiling of individual cells under different biological conditions.

278 ges in Ca(2+) signaling and contractility of individual cells under sustained application of either d

279 measure over 40 parameters simultaneously on individual cells using metal-chelating polymer (MCP) bas

280 recommend attempting to resolve isoforms in individual cells using scRNA-seq.

281 otein tyrosine phosphatase (PTP) activity in individual cells using self-assembled monolayers for mat

282 lation of the TIE and TRD to the mass of the individual cells were also analyzed for different hours

283 each NK cell after removal, secretions from individual cells were assessed.

284 PTP activities from thousands of individual cells were measured and their distributions a

285 the phage-host relationship on the level of individual cells, which has the potential of importantly

286 ent transcriptional regulatory inputs across individual cells, which is further complicated by largel

287 ach showing patterns of co-expression within individual cells, which were mainly not explicable by ch

288 ors exhibiting GD2 expression on <50% of the individual cells, while some tumors are essentially GD2-

289 partite viruses manage to efficiently infect individual cells with all segments, thus with the whole

290 lls and show that scPred is able to classify individual cells with high accuracy.

291 oration of cellular perturbations by tagging individual cells with RNA "barcodelets" to identify them

292 the biological sciences is to determine how individual cells with varied gene expression profiles an

293 ov-1 FLC frequently digitally reactivates in individual cells, with a probability that diminishes wit

294 However, obtaining time-resolved data from individual cells within a live vertebrate organism remai

295 econds and spatial precision to the level of individual cells within a population.

296 and extracellular traction forces acting on individual cells within an endothelial cell colony as we

297 ods to fully characterize drug efficacy from individual cells within cell populations.

298 anism that provides a selective advantage to individual cells within otherwise transcriptionally hete

299 d these with cell border markers to identify individual cells within the tissue.

300 ated with their borders are variable between individual cells, yet chromatin intermingling is enriche