ライフサイエンスコーパス: single cell

1 both sexes with computational modeling of a single cell.

2 ion 36 (CD36), in a spatiotemporal manner in single cells.

3 arge cell populations likely do not exist in single cells.

4 he expression of hundreds of chosen genes in single cells.

5 es and their interactions with the PM within single cells.

6 table for precise electroporation control in single-cells.

7 Here, we present a single-cell aggregation and integration (scAI) method to

8 Single-cell analyses of matched organoid cultures and na

9 water-in-oil droplet-based microfluidics for single cell analysis met problems.

10 metric and magnetophoretic methods; however, single cell analysis with the magnetophoretic mobility m

11 hat incorporates several of the most popular single-cell analysis algorithms into a flexible pipeline

12 ng datasets that hold the key for label-free single-cell analysis and, consequently, for differentiat

13 Thus, spatially resolved, single-cell analysis can characterize intratumour phenot

14 Here, using a modified method of single-cell analysis for somatic L1 insertions, we studi

15 Spatially resolved, single-cell analysis identified the phenotypes of tumour

16 Single-cell analysis is revealing increasing diversity i

17 rm FLOW-MAP analysis side by side with other single-cell analysis methods, to illustrate when it is a

18 In contrast, single-cell analysis of CD4(+) T cells demonstrates seve

19 Further, single-cell analysis of in vivo and in vitro cardiomyocy

20 f the unfolded protein stress response, with single-cell analysis of primary bone marrow revealing pe

21 ply many of the recently developed tools for single-cell analysis on flow cytometry data, as well.

22 bust, reproducible, and highly interpretable single-cell analysis platform that couples dominant patt

23 Most current methods in single-cell analysis rely on cell manipulation, potentia

24 Single-cell analysis reveals a specific shift from highl

25 inspired the development of high-dimensional single-cell analysis tools to comprehensively characteri

26 the chemical heterogeneity uncovered by the single-cell analysis while offering the ability to perfo

27 ave remained mysterious due to the limits of single-cell analysis.

28 the genomic and transcriptomic landscape of single cell and bulk RNA sequencing data.

29 eously monitor CDK4/6 and CDK2 activities in single cells and found that CDK4/6 activity increases ra

30 can reveal new forms of biological memory in single cells and suggests that non-genetic heritability

31 Our procedures may be applied to both single-cell and bulk RNA-seq.

32 Using single-cell and bulk TCR sequencing and structural affin

33 We provide single-cell and bulk transcriptome analyses of CD49f(+)

34 tion of refractory RA and the application of single-cell and integrated omics technologies to the ide

35 Integration of single-cell and spatial data mapped ligand-receptor netw

36 let microfluidic system: droplets containing single cells are immobilized in a two-dimensional (2D) a

37 To generate scMNase-seq libraries, single cells are isolated by FACS sorting, lysed and dig

38 sts from metagenomic libraries by processing single cells as many as 10(8) per day.

39 Using single-cell assays of HSC quiescence, stemness, differen

40 rway differentiation in vitro and provides a single-cell atlas of the developing human lung.

41 How best to project data across single-cell atlases is an open problem.

42 gment the heavily genomic and transcriptomic single-cell atlases with protein-level profiling.

43 dvanced the mechanistic understanding of AD, single cell-based molecular alterations are largely unkn

44 With the advent of single-cell-based technologies, a new 'worldview' is eme

45 The incorporation of the single cell biosensor and transient gene knockdown into

46 Mapping transposase-accessible chromatin in single cells by sequencing defined the transcription fac

47 Analysis of the NMBS applied to single cells, cell monolayers, and Drosophila ovarioles

48 urthermore, by combining these findings with single-cell chromatin accessibility (scATAC-seq) data, w

49 However, single-cell clonal expansion produces heterogeneous meth

50 On the other hand, manually annotating single cell clusters by examining the expression of mark

51 isobaric labeling approach (TMT-11plex), ~77 single cells could be analyzed per day.

52 A key missing aspect is that real single cell data usually has non-uniform uncertainty in

53 igenetic marks, time series experiments, and single cell data.

54 have been developed for marker selection on single cell data; most of them, however, are based on co

55 w, we focus on how biochemical, genomic, and single-cell data describe the regulatory steps of transc

56 more cells, enabling factorization of large single-cell data sets.

57 de a low-error, compressed representation of single-cell data that enables efficient large-scale comp

58 s by mass cytometry of 28 PTMs in >1 million single cells derived from small intestinal organoids rev

59 clude that the sizes of the non-backtracking single cell domains are most close to the sizes of compa

60 ochastic model constrained by a large set of single-cell E. coli flagellar synthesis data from differ

61 have combined two-photon Ca(2+) imaging and single-cell electrophysiology in awake behaving mice fol

62 spatial scale on diverse samples, including single cells, embryos and cleared tissue.

63 in-water double emulsion droplets serving as single-cell enzymatic micro-reactors and a commercially

64 ther, these results demonstrate the power of single-cell epigenomics to identify regulatory programs

65 nable such temporal analysis from multimodal single-cell experiments, we introduce an extension of th

66 ated analysis of chromatin accessibility and single-cell expression data shows that regulatory elemen

67 Surprisingly, through the analysis of single-cell expression studies and in situ hybridization

68 We sequenced more than 52,500 single cells from embryonic day 11.5 (E11.5) postembryon

69 identify regulatory genes in data sets from single cell gene expression and from abiotic stress trea

70 Here, using single-cell gene expression profiling and anatomical cir

71 a soluble TFR cell effector molecule through single-cell gene expression profiling.

72 tate this, we developed a novel simulator of single-cell genome evolution in the presence of CNAs.

73 We review the prospects of applying single-cell genome, transcriptome, epigenome, proteome,

74 Single-cell genomics has transformed our ability to exam

75 on biological systems, as well as searching single cell GES databases to identify novel network conn

76 Biophysical studies on single cells have linked cell mechanics to physiology, f

77 nnotation of compartmental domains in sparse single cell Hi-C matrices.

78 on of the chromatin compartmental domains in single cells Hi-C matrices.

79 pproach used to mitigate this issue, even in single-cell Hi-C data, is genome-wide averaging (piling-

80 luding the X chromosome), using an optimized single-cell high-throughput chromosome conformation capt

81 Given a single-cell image from one of the stages, ImageAEOT gene

82 ons, ranging from single-molecule sensing to single-cell imaging, has been made.

83 research we explore the use of microfluidic single-cell impedance spectroscopy in the field of calci

84 e, we show transcriptome profiling of 21,422 single cells-including cardiomyocytes (CMs) and non-CMs

85 ular interface mediate organized assembly of single cells into tissues and, thus, govern the developm

86 observation that alternative splicing among single cells is highly variable and follows a bimodal pa

87 Single-cell karyotype analysis indicates that these CNVs

88 tion between active and inactive bacteria at single cell level is urgently needed in many fields incl

89 action and osteogenic gene expression at the single cell level.

90 able to measure the kinase activities at the single cell level.

91 tes regarding the number of clusters and the single-cell level cluster assignments.

92 dissect the transcriptomic landscape at the single-cell level during renal injury and the resolution

93 is study, we analyzed polyclonal MBCs at the single-cell level from peripheral blood mononuclear cell

94 Recent sequencing studies at the bulk and single-cell level in humans and rodents provide new insi

95 ctivities and cell-state trajectories at the single-cell level in response to neuronal activation.

96 of MAP to explore metabolic profiles at the single-cell level makes it a valuable tool for basic sin

97 This allows assessing drug effects at the single-cell level within a complex 3D cell environment i

98 in the mouse blood and ischemic heart at the single-cell level, and reveal a process of local tissue

99 shifts have remained mostly unstudied at the single-cell level, due largely to engineering challenges

100 e the redox mechanism of cardiomyocytes at a single-cell level.

101 ncoded reporter to study TNF shedding at the single-cell level.

102 p after sleep deprivation at the network and single-cell level.

103 reported technique can be used to study the single-cell-level dynamics of EET not only on electrode

104 ultrasensitive analysis of bacteria at their single-cell levels within a 3 h procedure.

105 Single-cell longitudinal estimates of HCV clearance from

106 st evidence for a role for spectraplakins in single-cell lumen formation and branching.

107 Single-cell lysate in each microwell is "electrophoretic

108 et-specific CD8+ T cells using high-content, single-cell mass cytometry in combination with peptide-l

109 proaches to understanding decision-making in single cells may be abstracted one level further, to the

110 growth of the resulting conidia, which were single-cell monokaryotic progeny, was observed on the me

111 d (iii) The affected tissue is a homogeneous single cell monolayer, facilitating accurate transcripto

112 Single-cell mRNA sequencing revealed that systemic Akt1

113 Here, single-cell multi-omics analysis demonstrates a shared m

114 Despite the noisy nature of single cells, multicellular organisms robustly generate

115 Generating single-cell, multiparametric, longitudinal atlases and i

116 Single-cell mutation and phospho-protein analyses reveal

117 hose containing cells with good agreement to single-cell occupancies quantified via microscopy, estab

118 etween the epithelial lineages, we find that single cells of all lineages sort to the interior of ect

119 rocess, we use micromanipulation to position single cells of diverse lineages on the surface of defin

120 Single-cell or single-nuclei mRNA sequencing of dissocia

121 of the first examples of a virus infecting a single-celled organism that is itself an ectobiont of an

122 anism that is itself an ectobiont of another single-celled organism.IMPORTANCE Here, we present evide

123 conditioned media in organoid expansion and single-cell organoid outgrowth.

124 We used site-directed mutagenesis and single-cell patch-clamp to analyze the functional effect

125 city, meaning rare stochastic transitions of single-cell phenotype.

126 As one of the single-celled photosynthetic organisms that inhabit mari

127 The introduction of single-cell platforms inspired the development of high-d

128 ssues and from both plate- and droplet-based single-cell platforms.

129 idic platform that enables the quantitative, single-cell precision analysis of cell protrusion format

130 ,000 cancer and tumor microenvironment (TME) single-cell profiles exposed a rich and dynamic tumor ec

131 These efforts are propelled by advances in single cell profiling.

132 Using high-resolution single-cell profiling in tissue, we have uncovered the d

133 ssification scheme, several groups have used single-cell profiling to catalog DA neurons based on the

134 ftware tool that enables rapid evaluation of single-cell proteomic data and recommends instrument and

135 ce and is expected to be a powerful tool for single cell proteomics.

136 Single-cell proteomics can provide critical biological i

137 Lastly, we introduce Single-Cell Proteomics Companion (SCPCompanion), a softw

138 As a demonstration for single-cell proteomics, the autosampler was first applie

139 nucleotide variants and their expression in single cells provides a powerful novel approach to accur

140 First, even the highest quality single-cell recording studies find a fraction of the sti

141 Through single-cell recordings in behaving male and female C57BL

142 terized phenotypically by flow cytometry for single-cell resolution of distinct ILC subsets.

143 ile visualization of drug effects in vivo at single-cell resolution over days.

144 he profiling of multiple molecular layers at single-cell resolution, assaying cells from multiple sam

145 chanisms underlying primate ovarian aging at single-cell resolution, revealing new diagnostic biomark

146 bling studies of viral plaque formation with single-cell resolution.

147 py, establishing robust droplet screening at single-cell resolution.

148 ility to examine transcriptional profiles at single-cell resolution.

149 ll RNA sequencing, we examine mosaicism with single-cell resolution.

150 ability to dissect TE expression dynamics at single-cell resolution.

151 Data mining of human adult bulk and single-cell retinal transcriptional datasets revealed pr

152 control of neurogenesis, we have carried out single cell RNA sequencing of the zebrafish hindbrain at

153 s for meningioma therapy using live imaging, single cell RNA sequencing, CRISPR interference, and pha

154 ring is an essential step in the analysis of single cell RNA-seq (scRNA-seq) data to shed light on ti

155 onding FBN1+ FAP cell type was also found in single cell RNA-seq analysis in mouse.

156 ubtype-pooled single human muscle fibers and single cell RNA-seq of mononuclear cells from human vast

157 Here we use single cell RNA-seq to show that murine IFE differentiat

158 The Plant Single Cell RNA-Sequencing Browser, with its comprehensi

159 Single cell RNA-sequencing of activated B cells and cons

160 une cells across multiple mouse organs using single-cell RNA and antigen receptor sequencing and flow

161 Focusing on the developing limb, single-cell RNA data identified 25 candidate cell types

162 Here we describe barcodelet single-cell RNA sequencing (barRNA-seq), which enables s

163 Current approaches to single-cell RNA sequencing (RNA-seq) provide only limite

164 The development of single-cell RNA sequencing (scRNA-seq) has allowed high-

165 Single-cell RNA sequencing (scRNA-seq) has enabled the s

166 Single-cell RNA sequencing (scRNA-Seq) indicated that SL

167 Progress in single-cell RNA sequencing (scRNA-seq) provides an oppor

168 Here, we employed single-cell RNA sequencing (scRNA-seq) to examine the im

169 Using single-cell RNA sequencing (scRNA-seq), we have identifi

170 c devices have become widely used to perform single-cell RNA sequencing (scRNA-seq).

171 Single-cell RNA sequencing analyses detected activated B

172 Single-cell RNA sequencing and analytical approaches hav

173 We applied single-cell RNA sequencing and computational modelling t

174 Single-cell RNA sequencing and direct comparison to feta

175 n rare metastatic cells during seeding using single-cell RNA sequencing and patient-derived-xenograft

176 Using single-cell RNA sequencing and synovial tissue organoids

177 Single-cell RNA sequencing confirms the accumulation of

178 Using single-cell RNA sequencing coupled with high-resolution

179 iptomic basis of EC specificity, we analyzed single-cell RNA sequencing data from tissue-specific mou

180 We used single-cell RNA sequencing data generated by the Tabula

181 ic tissue were analyzed and categorized with single-cell RNA sequencing data to perform cluster ident

182 Single-cell RNA sequencing has emerged as a powerful too

183 Single-cell RNA sequencing identified 16 cell clusters,

184 Here, using single-cell RNA sequencing in human and mouse non-small-

185 e a universal sample multiplexing method for single-cell RNA sequencing in which fixed cells are chem

186 Single-cell RNA sequencing of five TNBCs revealed two ca

187 atch-clamp recording, biocytin staining, and single-cell RNA sequencing of more than 1,300 neurons in

188 imuli, we also analyzed data from a study of single-cell RNA sequencing of mouse cortical neurons.

189 ent of CF lung disease.Methods: We performed single-cell RNA sequencing of sputum cells from nine sub

190 Single-cell RNA sequencing of the immune compartment sho

191 Single-cell RNA sequencing of vascular cells in mice sug

192 l these important knowledge gaps, we perform single-cell RNA sequencing on two-day old schistosomula

193 ge in pre-processing data from droplet-based single-cell RNA sequencing protocols is distinguishing b

194 Microarray analysis and single-cell RNA sequencing revealed that a number of cyt

195 tic lineage tracing of mature adipocytes and single-cell RNA sequencing revealed that dermal adipocyt

196 Single-cell RNA sequencing revealed that epidermal devel

197 Single-cell RNA sequencing showed that SNP-IV induced st

198 Although single-cell RNA sequencing studies have begun to provide

199 First, we used single-cell RNA sequencing to generate a cellular landsc

200 employed stimulus-to-cell-type mapping using single-cell RNA sequencing to identify the cellular subs

201 We used single-cell RNA sequencing to profile human skeletal mus

202 Single-cell RNA sequencing uncovered three epicardial su

203 Integrated droplet- and plate-based single-cell RNA sequencing were used in the murine, reve

204 Here, we report for the first time in-depth single-cell RNA sequencing, combined with spatial transc

205 By custom single-cell RNA sequencing, we examine mosaicism with si

206 Using single-cell RNA sequencing, we found that in GA lesions

207 Using allele-specific single-cell RNA sequencing, we here estimate the two noi

208 Using bulk and single-cell RNA sequencing, we identify molecular change

209 Here, using single-cell RNA sequencing, we profiled the transcriptom

210 Using single-cell RNA sequencing, we show that these cells are

211 tional contributions of B cells via bulk and single-cell RNA sequencing, which demonstrate clonal exp

212 cal samples with the depth and resolution of single-cell RNA sequencing.

213 Droplet-based single-cell RNA-seq (dscRNA-seq) data are being generate

214 existing methods for linking microscopy and single-cell RNA-seq (scRNA-seq) have limited scalability

215 ts a regression-based approach that utilizes single-cell RNA-seq (scRNA-seq) or single-nucleus RNA-se

216 Using single-cell RNA-seq data, we showed that the core regula

217 Here we used multiplexed single-cell RNA-seq to profile 198 cancer cell lines fro

218 Single-cell RNA-sequencing (scRNA-seq) allows us to diss

219 Using single-cell RNA-sequencing (scRNA-seq) and genetic repor

220 Here, we integrated recently published single-cell RNA-sequencing (scRNA-seq) data from 727 per

221 We analyzed previously generated single-cell RNA-sequencing (scRNA-seq) data of gastric c

222 leverage human, non-human primate, and mouse single-cell RNA-sequencing (scRNA-seq) datasets across h

223 f the etiology of blinding diseases, we used single-cell RNA-sequencing (scRNA-seq) to analyze the tr

224 Mechanistically, single-cell RNA-sequencing analyses of a mesenchymal nic

225 cent studies combine two novel technologies, single-cell RNA-sequencing and CRISPR-Cas9 barcode editi

226 xpression of viral entry-associated genes in single-cell RNA-sequencing data from multiple tissues fr

227 By integrating single-cell RNA-sequencing data of mouse hearts at multi

228 ic gene expression from different tissues in single-cell RNA-sequencing data.

229 Surprisingly, single-cell RNA-Sequencing implicated glia, not neurons,

230 Single-cell RNA-sequencing of plaque immune cells reveal

231 By integrating CRISPR screens and single-cell RNA-sequencing profiling, we have uncovered

232 Single-cell RNA-sequencing revealed that Ang2 blocking r

233 Here, we employed single-cell RNA-sequencing to interrogate aging-related

234 Single-cell RNA-sequencing, ribosome-associated mRNA pro

235 Using a single cell RNAseq approach, we reveal that SGC are dist

236 ualization suite for major forms of bulk and single-cell RNAseq data in R. dittoSeq is color blindnes

237 We propose a method, Scellector (single cell selector), which uses haplotype information

238 DSP is capable of single-cell sensitivity within an ROI using the antibody

239 er, it remains difficult to isolate and then single-cell sequence such populations because of compoun

240 Single cell sequencing has become a powerful tool to stu

241 Single-cell sequencing (SCS) has impacted many areas of

242 Single-cell sequencing analysis revealed an axis of acti

243 f the BBB and BTB through the application of single-cell sequencing and imaging techniques, and the d

244 a, incorporation of other data types such as single-cell sequencing and proteomics, and improved use

245 ify which mutations to target in a follow-up single-cell sequencing experiment, thereby decreasing co

246 e cells as determined by lineage tracing and single-cell sequencing in development, adult, and diseas

247 nsidered as an excitatory neuron marker, our single-cell sequencing results reveal that Lm128C cells

248 As single-cell sequencing tools are providing increasing in

249 many studies simultaneously perform bulk and single-cell sequencing, some studies have analyzed initi

250 wide phasing and scaffolding capabilities of single-cell strand sequencing(1,2) with continuous long-

251 ell level makes it a valuable tool for basic single-cell studies as well as other screening applicati

252 The ability to analyze single cells substantially reduces the total number of c

253 e in situ hybridization (FISH) is a powerful single-cell technique that harnesses nucleic acid base p

254 Recent high-dimensional single-cell technologies such as mass cytometry are enab

255 ntified the phenotypes of tumour and stromal single cells, their organization and their heterogeneity

256 The mechanical phenotyping of single cells therefore offers many potential diagnostic

257 In single cell time-lapse imaging experiments, VHA(B) -eGFP

258 lytes in live cells at the single-organelle, single-cell, tissue section, and whole organism levels.

259 al and multimodal information collected from single cells to build predictive models for cell classif

260 scales from biochemical reaction networks in single cells to food webs of ecosystems.

261 f endogenous pathway activation, measured in single cells, to answer an unresolved question in the fi

262 Single-cell tracking could be used to determine the kine

263 We analyze the experimental data using single-cell tracking to calculate mean diffusivities and

264 Furthermore, single-cell trajectories reconstructed from both techniq

265 We develop a strategy to simulate single-cell transcriptional data from synthetic and Bool

266 Our work provides multi-tissue single-cell transcriptional landscapes associated with a

267 Single cell transcriptome analysis revealed various IL-1

268 We performed single-cell transcriptome analyses of 14,441 cells from

269 Using single-cell transcriptome analysis and antibody screenin

270 led knockin sequencing (PoKI-seq), combining single-cell transcriptome analysis and pooled knockin sc

271 Single-cell transcriptome analysis of Hh-deficient mesod

272 CIRCM), and TRM pools by lineage-tracing and single-cell transcriptome analysis.

273 y immune dysfunction, we performed the first single-cell transcriptome characterization of CF sputum.

274 intained, making possible the correlation of single cell transcriptomes with cell location, morpholog

275 Single-cell transcriptomes from dissociated tissues prov

276 circumvent these issues, we analyzed 45,334 single-cell transcriptomes from embryonic day (E)7.5, wh

277 ciated with post-MI HF (data set 2), whereas single-cell transcriptomes identified 15 gene-protein ca

278 These single-cell transcriptomic analyses of the shoot apex yi

279 Here we report a single-cell transcriptomic analysis of hematovascular de

280 Using single-cell transcriptomic analysis, we characterized th

281 e genome-wide association study results with single-cell transcriptomic data from the entire mouse ne

282 n algorithms, as demonstrated using existing single-cell transcriptomic data sets and new data modeli

283 Single cell transcriptomics technologies have vast poten

284 Using single-cell transcriptomics and chromatin accessibility,

285 al. use single-cell transcriptomics and epigenomics in mice and

286 Single-cell transcriptomics and immunostaining of both W

287 Single-cell transcriptomics from dissociated kidneys fac

288 Single-cell transcriptomics has been widely applied to c

289 Single-cell transcriptomics has radically improved our a

290 Single-cell transcriptomics of neocortical neurons have

291 sm for the observed inhibition, we performed single-cell transcriptomics on OSNs exhibiting specific

292 in health and ulcerative colitis (UC) using single-cell transcriptomics with T-cell receptor reperto

293 sal metazoan Hydra by using a combination of single-cell transcriptomics, immunochemistry, and functi

294 ction of bulk tissue DNA methylation data at single cell-type resolution for any solid tissue.

295 istic model using tumor spheroids instead of single cells under perfusion.

296 Based on recent experimental results for single cells, we derive a minimal length scale for the p

297 and sequencing of immunoglobulin genes from single cells, we find that 5-10% of gut-associated germi

298 synthetic picoeukayote (PPE) populations and single cells were analysed by sequencing of 16S rRNA gen

299 py for spatial mapping of metabolites within single cells, with the specific goal of identifying drug

300 ia can be visualized and quantified within a single cell without sectioning.