ライフサイエンスコーパス: transcriptomic

1 , natural genetic variation, proteomics, and transcriptomics.

2 holistic approach ranging from microscopy to transcriptomics.

3 st for single cell cloning, phenotyping, and transcriptomics.

4 phenotypes that are difficult to infer from transcriptomics.

5 isting neural taxonomies are based on either transcriptomic(3,4) or morpho-electric(5,6) criteria, as

6 ce microSPLiT (microbial split-pool ligation transcriptomics), a high-throughput scRNA-seq method for

7 and Transcript Distribution) which uses both transcriptomic abundances and parsimony of overall flux

8 ation opens with an abrupt and discontinuous transcriptomic activation in the epithelia, accompanied

9 The FHL2-GLI2 fusions result in transcriptomic activation of the Sonic Hedgehog (SHH) pa

10 ilepsy, and rescued cognitive impairment and transcriptomic alterations associated with chronic epile

11 VCP transgenic mouse model to understand the transcriptomic alterations induced by VCP under the card

12 Genome-wide transcriptomic analyses have revealed abundant expressed

13 ble therapeutic strategy, we performed brain transcriptomic analyses in 8-month-old animals from our

14 CoV-2 pathogenesis in macaques, we performed transcriptomic analyses of bronchoalveolar lavage and pe

15 Transcriptomic analyses of DICER1 deleted uteri or Ishik

16 Transcriptomic analyses of estrus stage uteri were condu

17 We performed integrated metabolomic and transcriptomic analyses of liver tissue from patients wi

18 In addition, recent genomic and transcriptomic analyses of several Orobanchaceae parasit

19 Transcriptomic analyses of the ovarian tumors from PGRB-

20 These single-cell transcriptomic analyses of the shoot apex yield insight

21 Transcriptomic analyses on endometrial cancers and precu

22 Transcriptomic analyses reveal downregulation of the ECM

23 Histologic and transcriptomic analyses revealed that Sfrp1 induced an e

24 Moreover, cell-type-specific transcriptomic analyses revealed transcription regulator

25 Chromatin immunoprecipitation and transcriptomic analyses suggest that PRDM14 cooperates w

26 rformed integrative methylomic, genomic, and transcriptomic analyses to characterize sites of DNA met

27 Lipidomic and transcriptomic analyses were performed in human tricuspi

28 Through combined proteomic and transcriptomic analyses, we identified numerous autophag

29 ourse, conducted in parallel to time-matched transcriptomic analyses.

30 Complementing our metabolomics results, our transcriptomics analyses also revealed significant alter

31 Transcriptomic analysis (RNA-seq) of tomato demonstrated

32 Transcriptomic analysis and ChIP-PCR together demonstrat

33 Transcriptomic analysis differentiated 27 from the bench

34 Transcriptomic analysis further confirmed increased PPAR

35 Using a transcriptomic analysis in conjunction with qPCR, we fin

36 Transcriptomic analysis in this setting highlighted unde

37 The combination of our bioassays and the transcriptomic analysis indicate that intact SA signalli

38 Transcriptomic analysis linked elevated injury to increa

39 Here, we present single-cell transcriptomic analysis of >100,000 viral antigen-reacti

40 Consistent with patient data, transcriptomic analysis of BAP1 mutant UM cell lines als

41 These studies included a detailed transcriptomic analysis of changes in ectoderm and mesen

42 Transcriptomic analysis of cultured hepatocyte and HCC c

43 Conducting transcriptomic analysis of developing leaves in the WT a

44 Here we report a single-cell transcriptomic analysis of hematovascular development in

45 EC clonal and network formation, as well as transcriptomic analysis of isolated ECs.

46 Transcriptomic analysis of multiple myc mutants confirme

47 Transcriptomic analysis of ribosomal protein S6 kinase A

48 imitations and remaining questions regarding transcriptomic analysis of sex differences in ASD.

49 Furthermore, transcriptomic analysis of wild-type and Nolz1(-/-) muta

50 We performed transcriptomic analysis on acutely UV-exposed human skin

51 compartments, we performed single-cell (sc) transcriptomic analysis on human GC B cells and identifi

52 Transcriptomic analysis revealed alterations in the pyri

53 Focused transcriptomic analysis revealed induction of innate imm

54 the human menopausal transition, results of transcriptomic analysis revealed stage-specific shifts i

55 Moreover, transcriptomic analysis reveals that preneoplastic liver

56 Cortex-wide transcriptomic analysis shows direct alignment between t

57 Transcriptomic analysis suggested that ES24 has a comple

58 Using disease bioassays and transcriptomic analysis we show that intact SA-signallin

59 assays in vitro, whereas flow cytometry and transcriptomic analysis were used to assess further chan

60 from animals expressing neuronal xbp-1s for transcriptomic analysis, revealing a striking remodeling

61 Using single-cell transcriptomic analysis, we characterized the heterogene

62 cell suspensions was used for sequencing and transcriptomic analysis.

63 uman brain, we have performed single-nucleus transcriptomics analysis of >110,000 neuronal transcript

64 E4's role in AD pathogenesis, we performed a transcriptomics analysis of APOE4 vs. APOE3 expression i

65 Genome-wide spatial transcriptomics analysis provides an unprecedented appro

66 ulated Raman scattering (SRS) microscopy and transcriptomics analysis, we identify the fatty acid syn

67 established across species and cell types by transcriptomic and biochemical approaches, but their ant

68 Transcriptomic and chromatin immunoprecipitation analysi

69 Transcriptomic and elemental analyses revealed that this

70 mitophagy activity and displayed functional, transcriptomic and epigenetic characteristics of termina

71 rgeted assessments of the cell type-specific transcriptomic and epigenetic effects of dopamine deplet

72 iHCs exhibit hair cell-like morphology, transcriptomic and epigenetic profiles, electrophysiolog

73 issecting cellular heterogeneity within both transcriptomic and epigenomic layers and understanding t

74 fied correspondences between mouse and human transcriptomic and epigenomic patterns.

75 Simultaneous measurements of transcriptomic and epigenomic profiles in the same indiv

76 nvolute cellular heterogeneity from parallel transcriptomic and epigenomic profiles.

77 Transcriptomic and functional enrichment analyses reveal

78 Detailed transcriptomic and immunophenotypic analyses of IL-33-ex

79 nd controls (n = 19), and perform chromatin, transcriptomic and interaction profiling.

80 aim of this study was to decipher the local transcriptomic and lipidomic consequences of rs174547 in

81 Here, we analysed transcriptomic and metabolite responses of two cucumber

82 Transcriptomic and metabolomic analyses show that alpha2

83 Advances in genomic, transcriptomic and metabolomic tools for conifers have i

84 genomic resources with gene annotations and transcriptomic and proteomic data for six Nannochloropsi

85 lternative splicing is a prevalent source of transcriptomic and proteomic diversity in human populati

86 Genomic, epigenomic, transcriptomic and proteomic landscapes have now been ma

87 nlesional explants with IL-1beta resulted in transcriptomic and proteomic profiles similar to those o

88 onduct phosphoproteomics in conjunction with transcriptomic and proteomic profiling using fly heads.

89 The transcriptomic and proteomic signatures of ChP-CSF organ

90 hances of obtaining high-quality single-cell transcriptomic and repertoire data from human PBMCs in a

91 By single-cell transcriptomics and bioinformatics, both signaling and c

92 Using single-cell transcriptomics and chromatin accessibility, we gained a

93 subgroups of critical illness based on serum transcriptomics and derived immune cell fractions, with

94 al. use single-cell transcriptomics and epigenomics in mice and human sample

95 e-cell RNA sequencing, combined with spatial transcriptomics and immunohistochemistry, to comprehensi

96 Single-cell transcriptomics and immunostaining of both WT and DKO ER

97 ughput and DR subdomain-targeted single-cell transcriptomics and intersectional genetic tools to map

98 genetic studies and available information on transcriptomics and metabolomics.

99 ies of seed maturation regulators, combining transcriptomics and network analysis, suggest the signif

100 treatment efficacy by integrating genomics, transcriptomics and protein profiling including modifica

101 Unbiased transcriptomics and proteomics analysis on cytokine-prod

102 cases incorporating phenotypic, functional, transcriptomic, and genomic studies at sequential time p

103 We used growth, transcriptomic, and metabolite analysis to characterize

104 metabolic network that incorporates genetic, transcriptomic, and metabolomic data.

105 Although recent genomic, transcriptomic, and proteomic data proved the presence o

106 in genomic content but rather by epigenomic, transcriptomic, and proteomic heterogeneity.

107 technological advances, including serology, transcriptomics, and metabolomics, have provided new ins

108 everse genetics, quantitative N-terminomics, transcriptomics, and physiological assays to characteriz

109 the complex relationships between genomics, transcriptomics, and proteomics requires the development

110 An integrative comparative transcriptomic approach on six sugar beet varieties show

111 n molecular signatures were analyzed using a transcriptomic approach.

112 Transcriptomic approaches have provided a growing set of

113 Here, we combine genomic and transcriptomic approaches to describe the landscape of e

114 Using transcriptomic approaches, we also identified a claustru

115 Based on combined proteomic and transcriptomic approaches, we report that the Ig superfa

116 Using epigenomic and transcriptomic approaches, we sought to distinguish the

117 hen "omics" tools (genomics, proteomics, and transcriptomics) are applied to manipulated cell lines a

118 We describe a human single-nuclei transcriptomic atlas for the substantia nigra (SN), gene

119 Transcriptomics-based phenotype prediction benefits from

120 To investigate the transcriptomic basis of EC specificity, we analyzed sing

121 Comparative transcriptomics between differentiating human pluripoten

122 Comparative transcriptomics between low- and high-acylsugar-producin

123 ist of high confidence (core) reactions from transcriptomics, but parameters related to identificatio

124 the global histone mark based epigenomic and transcriptomic cartogram of SCC25, a representative cell

125 iocytes that undergo endosymbiosis-dependent transcriptomic changes affecting cell motility, cell adh

126 Early transcriptomic changes and predicted upstream regulators

127 High expression of TRIM37 induced transcriptomic changes characteristic of a metastatic ph

128 bust method for the identification of global transcriptomic changes in rare metastatic cells during s

129 ferentially active TFs, yet find very little transcriptomic changes in steady-state.

130 indings greatly advance the understanding of transcriptomic changes in the brain of alcohol-dependent

131 t into TR pathogenesis, we characterised the transcriptomic changes involved in feline TR by sequenci

132 We found that the largest transcriptomic changes occur in distinct neuronal subtyp

133 observed temporal and regional differences, transcriptomic changes were shared across first- and sec

134 d gene ontology analysis was used to examine transcriptomic changes with cold storage.

135 Transcriptomic changes, including NPPB levels, directly

136 in open and closed chromatin with associated transcriptomic changes.

137 duces mechanical hypersensitivity and global transcriptomics changes in a sex-specific manner.

138 sequencing revealed remarkable similarity of transcriptomic clusters between mouse and human lesions

139 o their glomerular types, demonstrating that transcriptomic clusters correspond well with anatomicall

140 single-cell RNA sequencing, we identified 33 transcriptomic clusters for ORNs and mapped 20 to their

141 a general framework relating the genomic and transcriptomic components in a microbiome, we performed

142 Transcriptomics confirms transposon-mediated effects on

143 Using paired, cell-specific transcriptomic data and causal inference testing, we ide

144 While network analysis of transcriptomic data can provide insights via co-expressi

145 tics pipelines for the analysis of bacterial transcriptomic data commonly ignore non-coding but funct

146 Analysis of transcriptomic data demonstrates extensive epigenetic ge

147 olomic data were integrated with whole blood transcriptomic data for each participant at diagnosis an

148 Exploring single-cell transcriptomic data for the mouse cortex, we identified

149 Analysis of transcriptomic data from autopsy cases and animal models

150 Our approach of analyzing transcriptomic data from different populations and patie

151 Furthermore, by integrating transcriptomic data from in vitro experiments and in pro

152 e association study results with single-cell transcriptomic data from the entire mouse nervous system

153 logical data analysis using human epithelial transcriptomic data from the U-BIOPRED cohort identified

154 ings with datasets from wounded skin and our transcriptomic data on cuSCC using functional pair analy

155 analysis combining cytology with genomic and transcriptomic data reveals biological characteristics o

156 Pathway analysis of transcriptomic data reveals that downregulated pathways

157 , as demonstrated using existing single-cell transcriptomic data sets and new data modeling drug-resi

158 analysis and functional analysis of relevant transcriptomic data sets using a common approach, indepe

159 Transcriptomic data support the concept that functional,

160 We used pan-genomic HIF-binding and transcriptomic data to identify a novel long noncoding R

161 use proteomic data with patient pretreatment transcriptomic data to identify molecular features disce

162 e genome-wide association studies (GWAS) and transcriptomic data to showcase their improved statistic

163 bined analysis of previously published blood transcriptomic data with new data from a prospective hum

164 The integration of the transcriptomic data with regulome revealed the differenc

165 rated that BEM is applicable to all kinds of transcriptomic data, including bulk RNA-seq, single-cell

166 However, analysis of transcriptomic data, the cause of biological and patholo

167 tant way to analyze coregulation patterns in transcriptomic data, which can reveal the tumor signal p

168 ng 6 (ZDHHC6), was characterised using whole transcriptomic data.

169 hrough analysis of primary tumor genomic and transcriptomic data.

170 ctory of LOAD disease progression from brain transcriptomic data.

171 s upon prior methods used to analyze spatial transcriptomics data and can propose novel pairs of extr

172 ature, we performed network deconvolution of transcriptomics data derived from tissues possessing mot

173 antified by ELISA (n = 181) and examined via transcriptomics data from external cohorts.

174 Transcriptomics data from Lake Rotsee (Switzerland) show

175 ics approach of patient-derived genomics and transcriptomics data suggested only minimal effects on e

176 copy number variations (CNVs) not evident in transcriptomics data.

177 are then combined with the cell line-derived transcriptomic datasets through elastic net regression a

178 ulk RNA-seq, single-cell RNA-seq and spatial transcriptomic datasets.

179 chnical processes that give rise to observed transcriptomic datasets.

180 ption factors (TFs) and cofactors that drive transcriptomic differences between samples is challengin

181 tigation of inheritance patterns that govern transcriptomic differences between these genetically div

182 Transcriptomic differences between wild and domesticated

183 are poorly understood, we aimed to identify transcriptomic differences in primary tumour and peritum

184 We also evaluated and validated transcriptomic differences in the primary tumours of obe

185 lysis and hierarchical clustering tested for transcriptomic distinctiveness between groups, effect of

186 otein response and here we show much broader transcriptomic effects.

187 drug resistance: inference based on genomic, transcriptomic, epigenomic and/or proteomic analysis of

188 e respective mouse lines was investigated by transcriptomic, epigenomic, and phenotypic analyses.

189 ing human and rodent data from proteomic and transcriptomic experiments in the areas of cancer, stem

190 olecular pathways by integrating genomic and transcriptomic features of 1780 breast cancers and highl

191 ve improvements in clinical, histologic, and transcriptomic features of psoriasis.

192 ing morphological, electrophysiological, and transcriptomic features to classify interneurons in the

193 iking interneurons, consistent with previous transcriptomic findings of miR-128 in regulating gene ne

194 ork to enable a comprehensive Functional Iso-Transcriptomics (FIT) analysis, which is effective at re

195 Single-cell transcriptomics from dissociated kidneys facilitated the

196 Neurons in the extremes of this transcriptomic gradient express mutually exclusive marke

197 terogeneity in the TRN is characterized by a transcriptomic gradient of two negatively correlated gen

198 Single-cell transcriptomics has been widely applied to classify neur

199 Single-cell transcriptomics has radically improved our ability to ch

200 evelopments in the emerging field of spatial transcriptomics have opened up an unexplored landscape w

201 Thus, oxidative stress transcriptomics identified neurotoxic CNS innate immune

202 d uterus of patients with LAM, sharing close transcriptomic identity.

203 Hydra by using a combination of single-cell transcriptomics, immunochemistry, and functional experim

204 Through the integration of transcriptomics, in situ hybridization and immunohistoch

205 Coupling pharmacologic data with genomic and transcriptomic information, we showed that Prima-1(Met)

206 al ureteric obstruction model to dissect the transcriptomic landscape at the single-cell level during

207 However, the transcriptomic landscape of central nervous system (CNS)

208 We surveyed the single-cell transcriptomic landscape of ovaries from young and aged

209 ization and visualization of the genomic and transcriptomic landscape of single cell and bulk RNA seq

210 ng analysis of mouse PROM1(+) cells, reveals transcriptomic landscapes indicative of their identities

211 g variants, here we establish epigenomic and transcriptomic landscapes of primary OCs using H3K27ac C

212 and reveal their synergistic effects at the transcriptomic level through the regulation of important

213 racterized at histopathological, immune, and transcriptomic level to identify the unique features of

214 At the transcriptomic level, photosynthesis was the primary fun

215 s of eyestalk ablation and live feeds at the transcriptomic levels.

216 fer expression state of genes from replicate transcriptomic libraries.

217 ood molecular profiles including proteomics, transcriptomics, lipidomics, metabolomics, autoantibodie

218 Combining genomics, transcriptomics, metabolomics, and biochemistry, we iden

219 The versatility of transcriptomic methods to yield rich, high-resolution, i

220 The S63 transcriptomic metric (AUC 0.80) outperformed clinical m

221 The transcriptomic metric has been operationalized on an Foo

222 racterised by an immune dysregulation at the transcriptomic, molecular and cellular levels, creates o

223 glycolate metabolism, performing comparative transcriptomics of autotrophic growth under low and high

224 Single-cell transcriptomics of neocortical neurons have revealed mor

225 bserved inhibition, we performed single-cell transcriptomics on OSNs exhibiting specific response pro

226 We applied integrative transcriptomics on six varieties exhibiting different le

227 thers (ie, adipose, heart) have considerable transcriptomic overlap with ECs from other tissues.

228 Previous studies have identified transcriptomic patterns in the brain associated with alc

229 Cardiac inflammation along with a transcriptomic profile of high expression of combined pr

230 In this study, we analysed the transcriptomic profile of P. aeruginosa cells isolated f

231 QD394 shows a transcriptomic profile remarkably similar to napabucasin

232 eted uteri or Ishikawa cells revealed unique transcriptomic profiles and global miRNA downregulation.

233 To achieve this, we use inexpensive transcriptomic profiles derived from human cell lines af

234 nfer latent developmental processes from the transcriptomic profiles of cells at various developmenta

235 high dependence of CDR on tumor genomic and transcriptomic profiles of individual patients.

236 Transcriptomic profiles were predictive of outcomes from

237 f TPR causes rapid and pronounced changes in transcriptomic profiles.

238 n, energy levels, the lipid environment, and transcriptomic profiles.

239 ients were harvested for immune phenotyping, transcriptomic profiling and functional assays.

240 Here, we perform deep transcriptomic profiling at high temporal resolution as

241 astoma molecular subtypes through the use of transcriptomic profiling data.

242 , minimally invasive alternative, but global transcriptomic profiling in early pediatric AD is lackin

243 Phenotypic and transcriptomic profiling of c-Maf-deficient CCR6(-) ILC3

244 Transcriptomic profiling of cortical neural progenitor c

245 ing (scRNA-seq) has enabled the simultaneous transcriptomic profiling of individual cells under diffe

246 Comprehensive genomic and transcriptomic profiling of untreated primary RMC tissue

247 Transcriptomic profiling provides a robust and objective

248 Comprehensive genomic and transcriptomic profiling revealed deregulation of variou

249 s, molecular/cell biology, pathogenicity and transcriptomic profiling.

250 Combined analysis of transcriptomic, protein, and immunohistochemical data in

251 is of cell- and tissue-specific models using transcriptomic, proteomic, and kinetic data.

252 Transcriptomic, proteomic, and phospho-proteomic profili

253 genome sequencing, host immune response, and transcriptomic, proteomic, metabolomic and epigenetic si

254 In contrast to transcriptomics, proteomics and metabolomics generate da

255 High-throughput technologies for genomics, transcriptomics, proteomics, and metabolomics, and integ

256 single nucleotide polymorphisms with AVNFH, transcriptomics, proteomics, metabolomics, biophysical,

257 R and mass spectrometry imaging, microscopy, transcriptomics, proteomics, metabolomics, lipidomics, i

258 rmed using the alcoholic liver disease (ALD) transcriptomic public dataset.

259 osomal RNA (rRNA), which otherwise dominates transcriptomic reads.

260 ite-sex partner for 24 hours or 3 weeks, and transcriptomic regulations in the nucleus accumbens were

261 The transcriptomic representation learned by HE2RNA can also

262 over conventional biopsies, including better transcriptomic resolution of skin cells, combined with p

263 The genomic and transcriptomic resources of three Echinochloa species an

264 assembly together with companion genomic and transcriptomic resources will enable the development of

265 Cs samples were analyzed by metabolomics and transcriptomics, respectively.

266 Our recent study evaluated the transcriptomic response occurring in rice roots during N

267 e that Klf9 contributes significantly to the transcriptomic response to chronic cortisol exposure, me

268 The transcriptomic response to desiccation identified four s

269 Herein, we explored the physiological and transcriptomic responses of the clam hosts and their pho

270 cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene E

271 the chronic phase of infection show an early transcriptomic signature akin to that of established T c

272 sis subclassification system, which includes transcriptomic signatures as well as other biological an

273 MerTK(pos)LYVE1(pos)) with unique remission transcriptomic signatures enriched in negative regulator

274 lterations are key factors in specifying the transcriptomic signatures of [SWI(+)] cells.

275 exity including the number of cell types and transcriptomic signatures of each cell type.

276 fined "M1" macrophage and "M1"/"M2" ratio by transcriptomic signatures using xCell.

277 ophoresis to augment the heavily genomic and transcriptomic single-cell atlases with protein-level pr

278 We performed transcriptomic, sphingolipid, and protein analyses to ev

279 pects of their biology, numerous genomic and transcriptomic studies have been performed, generating m

280 Recent meta-transcriptomic studies have uncovered thousands of leviv

281 ge of sepsis response subphenotypes based on transcriptomic studies of circulating leukocytes, specif

282 Transcriptomic studies with RND efflux-negative V. chole

283 urrounding the interpretation of bulk tissue transcriptomic studies.

284 tive matrix factorization identified 3 HFpEF transcriptomic subgroups with distinctive pathways and c

285 ta generated from various spatially resolved transcriptomic techniques.

286 Single cell transcriptomics technologies have vast potential in adva

287 Single-cell transcriptomics, the ability to track individual T cell

288 ve applied transgenics, lineage-tracing, and transcriptomics to help decipher the distinct roles of t

289 , we integrated chromatin accessibility with transcriptomics to identify putative enhancer-gene linka

290 We applied single-cell transcriptomics to map the heterogeneity of sinusoid-ass

291 an anteroposterior axis, and we use spatial transcriptomics to show that they exhibit patterned gene

292 Here we examine how specific transcriptomic types of mouse prefrontal cortex (PFC) pr

293 Leveraging high-throughput transcriptomics we identify NMD targets transcriptome-wi

294 Using RNA-sequencing transcriptomics we investigated lung gene expression res

295 Using transcriptomics, we found that components of the Fibrobl

296 Using single-cell transcriptomics, we identified a tissue-specific core si

297 a combination of whole-genome sequencing and transcriptomics, we showed that tolerance could be attri

298 Coupling transcriptomics with genetics, we show that emerging hai

299 We have integrated transcriptomics with histomorphological scores, identifi

300 nd ulcerative colitis (UC) using single-cell transcriptomics with T-cell receptor repertoire analysis