ライフサイエンスコーパス: gene expression level

1 whilst no association was detectable at the gene expression level.

2 id not restore full agonist responses at the gene expression level.

3 l tool to discover cellular heterogeneity at gene expression level.

4 s non-negligible noise, which increases with gene expression level.

5 r signatures of directional selection at the gene expression level.

6 mine if the study drug had any effect at the gene expression level.

7 nsights into the genetics of chickens at the gene expression level.

8 ly half (53%) were associated with decreased gene expression level.

9 ng non-coding regions that may be regulating gene expression levels.

10 ntations will be more robust to noise in the gene expression levels.

11 ents that drive cell-type or cohort-specific gene expression levels.

12 through changes both in protein sequence and gene expression levels.

13 - 2% of heritability was mediated by assayed gene expression levels.

14 on these phenotypes in relation to foraging gene expression levels.

15 diseases are caused by mutations that alter gene expression levels.

16 in SR-BI(-/-) embryos and normalized ROS and gene expression levels.

17 ological studies, assessment of protein, and gene expression levels.

18 y, is not dependent on Set1 altering overall gene expression levels.

19 UMI counts are not an unbiased estimator of gene expression levels.

20 orter gene assays confirmed that they affect gene expression levels.

21 ly measured in sample-sample correlations of gene expression levels.

22 each other via chromatin folding and affect gene expression levels.

23 ify associations between smoking and altered gene expression levels.

24 internal) and another subsystem's (external) gene expression levels.

25 rray are two main technologies for profiling gene expression levels.

26 g IU/L, which were inversely correlated with gene expression levels.

27 respectively) as accurately as the measured gene expression levels.

28 , roughly on a par with variants that affect gene expression levels.

29 ntial downstream effects, such as changes in gene expression levels.

30 onstrate how an HPT variation can affect the gene expression levels.

31 density lipoprotein and elevated antioxidant gene expression levels.

32 provides powerful estimators for evaluating gene expression levels.

33 tion pathway genes corresponded to decreased gene expression levels.

34 at associate with both chronological age and gene expression levels.

35 exons that may function directly to control gene expression levels.

36 ans to reprogram chromatin state and to hone gene expression levels.

37 ity mediated by the cis genetic component of gene expression levels.

38 if the same variant influences both DNAm and gene expression levels.

39 y protein expression of MT-I/II reflect MT2A gene expression levels.

40 ination is common and might in turn regulate gene expression levels.

41 alysis of neurons divided by Immediate Early Gene expression levels.

42 on putative regulatory element activity and gene expression levels.

43 es and plays an important role in regulating gene expression levels.

44 rectly correlates with Slxl1 gene dosage and gene expression levels.

45 are productively processed across different gene expression levels.

46 is and is modulated by stress conditions and gene-expression levels.

47 scription factor and DNA and consequently on gene-expression levels.

48 and is significantly correlated with higher gene expression level, a phenomenon also found in rice b

49 Here we describe genetic effects on gene expression levels across 44 human tissues.

50 a pathway based on the relative rankings of gene expression levels across a set of reference samples

51 x) project aims to characterize variation in gene expression levels across individuals and diverse ti

52 mpared with that detected through the use of gene expression levels alone.

53 The lack of LMO2 resulted in altered gene expression levels already at the haemangioblast sta

54 art site allows for specific and sustainable gene-expression level alterations in tumor cells in vitr

55 Gene expression levels altered by Pg LPS were determined

56 pecific polyTE insertion genotypes to B cell gene expression levels among 445 individuals from 5 huma

57 We applied linear mixed models (LMM) to the gene expression level and constructed likelihood ratio t

58 level) that considers the dependence between gene expression level and its variance (dispersion) and

59 rating whole blood TCR gamma constant region gene expression levels and age and sex (R(2)=0.12, P<1x1

60 phorylation, alongside reduction in absolute gene expression levels and cell size.

61 We demonstrate that sex influences gene expression levels and cellular composition of tissu

62 e-specific mutation profiles associated with gene expression levels and chromatin states.

63 TCR gamma constant region gene expression levels and clinical data of a whole bloo

64 r protein domain composition, correlation to gene expression levels and developmental integration to

65 nt associations between genetic variants and gene expression levels and found that the network struct

66 Both gene expression levels and homoeologous gene expression

67 of posttranscriptional regulators determine gene expression levels and how dysregulation of 3' UTR-m

68 BER gene expression levels and IFN treatment responses were

69 genome-wide method capable of capturing both gene expression levels and isoform diversity at the sing

70 Is associated with eQTLs and sQTLs can alter gene expression levels and isoform proportions, respecti

71 We studied gene expression levels and lung function in the Coronary

72 e used to determine differences in apoptotic gene expression levels and multiplex ligation-dependent

73 oach allows TREs to be assayed together with gene expression levels and other transcriptional feature

74 oops act as molecular rheostats to fine-tune gene expression levels and physical responses.

75 y performing an association analysis between gene expression levels and post-treatment tumor volume c

76 We found that the correlation between gene expression levels and profiled R-loop peak levels w

77 ional advantages by simultaneously measuring gene expression levels and profiling the immune-receptor

78 ch was associated with an increase of KLOTHO gene expression levels and serum KLOTHO concentrations.

79 The relationships between gene expression levels and sputum cell differentials or

80 g frame altering genomic variants can impact gene expression levels and the structure of protein prod

81 Vertex-wise maps of the association between gene expression levels and thickness across the cortex s

82 n; and showed the lowest metastasis-specific gene expression levels and TP53 mutation rates.

83 ERCA2 (0.77-fold, P=0.009) and mitochondrial gene expression levels and upregulation of genes related

84 itiation are independently controlled at the gene-expression level and that division processes exclus

85 ficant alterations in DNA copy numbers (CN), gene expression levels, and DNA methylation profiles.

86 sage-zero cultured BM-MSCs were analyzed for gene expression levels, and functional assays were condu

87 r primary cilia, exhibits location-dependent gene expression levels, and genetic ablation of ACIII dr

88 the 5' and 3' ends of genes, associated with gene expression levels, and significantly overlapped wit

89 heritable genetic factors influence SERPING1 gene expression levels, and that these associations are

90 immune cell proportions, cell type-specific gene expression levels, and the gene expression response

91 rular and tubular injury at the cellular and gene expression levels, and to confer exceptional therap

92 t that of each minor TSS decreases, with the gene expression level; and (iii) cis-elements for major

93 microbiota and how this is regulated at the gene expression level are critical questions.

94 Compared with the noncore, core gene expression levels are also similar across genetic b

95 vealed that bile acid synthesis and fibrosis gene expression levels are increased in chow-fed DKO mic

96 se results are compatible with a model where gene expression levels are modulated by the levels of th

97 The highest gene expression levels are often achieved through a nove

98 Genetic variants affecting gene-expression levels are a major source of phenotypic

99 contrast, molecular phenotype data, such as gene expression levels, are generally assumed to be free

100 ci (eQTLs), genetic variants associated with gene expression levels, are identified in eQTL mapping s

101 showed an overall positive correlation with gene expression level as well as prominent associations

102 tative relationship between miRNA and target gene expression levels as a function of parameters, incl

103 Utilizing the gene expression levels as a proxy, we have identified th

104 dentify distance to the Xist locus and prior gene expression levels as key determinants of silencing

105 ity levels were correlated to the respective gene expression levels as well as to the respective rece

106 Physiological mechanisms, like gene expression levels, as demonstrated in some Campylom

107 eq) can be used to characterize variation in gene expression levels at high resolution.

108 Gene expression levels at HPV integration sites were sta

109 gulatory regions is likely to also influence gene expression levels at these loci.

110 hnical noise and explicitly compute the true gene expression levels based on spike-in ERCC molecules.

111 esources for exploring the balance of global gene expression levels between excitatory AMPA receptors

112 ysis of chromosomal aberrations by comparing gene expression levels between normal and aneuploid samp

113 s the question to what drives differences in gene expression levels between subgenomes.

114 Comparison of gene expression levels between SUM149 cells with ERK2 or

115 nalysis which not only examined differential gene expression levels but could also detect differences

116 (BL) on morphological, immunophenotypic and gene-expression levels but lacking the IG-MYC translocat

117 ays to overcome limitations of transient/low gene expression levels, but also highlights the fact tha

118 ked many of these SNPs to human traits or to gene expression levels, but rarely with sufficient resol

119 Therefore, exogenous control of gene expression levels by administration of a nontoxic i

120 However, gene expression levels by themselves do not reflect the

121 ds were subjected to pHT 7.9 for 3 days, and gene expression levels, calcification and respiration ra

122 data suggest that cells with high basal Oas gene expression levels can activate RNase L and thereby

123 Here, we describe how gene expression levels can be efficiently acquired with

124 interspecies and inter-tissue differences in gene expression levels can only modestly be accounted fo

125 Within any given tissue, gene expression levels can vary extensively among indivi

126 ross individuals and cell types by measuring gene expression levels, chromatin accessibility, and DNA

127 By studying the genetic variation affecting gene expression levels (cis expression quantitative trai

128 Staging cells along a continuum of gene expression levels combined with single-cell RNA-seq

129 emonstrate that mammalian cells modify ORMDL genes expression levels coordinately to regulate the de

130 e further determined that sex differences in gene expression levels could be related to sex differenc

131 l, evaluated the association of pretreatment gene expression levels defined using RNA sequencing with

132 ified 5 additional genetic loci with imputed gene expression levels differing between cases and contr

133 on, deregulated histone acetylation, altered gene expression levels, distorted microRNA profiles, and

134 Prediction of gene expression levels driven by regulatory sequences is

135 primarily focused on sources of noise at the gene expression level due to limitations of existing noi

136 e most sensitive to noise: a slight shift in gene expression levels due to a repeated measurement wil

137 ypes, they describe the intrinsic 'noise' in gene expression levels due to limitations in experimenta

138 ues to be the main workhorse for quantifying gene expression levels due to technical simplicity and l

139 haracterised E3 ligases, MuRF1/MAFbx, at the gene expression level during atrophy, recovery from atro

140 orrelated with an increase in IFN-stimulated gene expression levels during HEV replication.

141 ed with this approach gave rich diversity of gene expression levels, dynamic ranges and ligand sensit

142 evels, including directional growth but also gene expression levels, dynamics, and regionalization, a

143 Gene expression level dysregulation was confirmed for ei

144 lationship between histone modifications and gene expression levels either failed to capture combinat

145 nificantly associated with both variation in gene expression levels (eSNPs) and asthma risk.

146 or transcription initiation and termination, gene expression levels estimated based on RNA-seq data a

147 genotypes showed a very different background gene expression level even without A. psidii infection.

148 strongly associated with variations in brain gene expression levels (expression quantitative loci, or

149 g for associations between DNA genotypes and gene expression levels, expression quantitative trait lo

150 highly correlated at the DNA methylation and gene expression levels, featuring ectopic expression of

151 We find that local genetic variation affects gene expression levels for the majority of genes, and we

152 n = 135,458 cases, n = 344,901 controls) and gene expression levels from 21 tissue datasets (brain; b

153 tion between the study trait and the imputed gene expression levels from cis-acting expression quanti

154 gulation that makes it possible to calculate gene expression levels from DNA regulatory sequence.

155 There was a transitional increase in Gli-1/2 gene expression levels from DP, DN to TS subpopulations,

156 this approach is to build a model to impute gene expression levels from genotypes by using samples w

157 Prediction of gene expression levels from regulatory sequences is one

158 These factors were associated with gene expression levels from RNA sequencing by using gene

159 Differences in reporter gene expression levels from the NP and GPC loci were con

160 as correlated with that of IL6R, we analyzed gene expression levels generated for 373 human lymphobla

161 Both gene expression levels (GEs) and copy number alterations

162 se and missing data, but also predict unseen gene expression levels (GEXs).

163 Basal gene expression levels have been shown to be predictive

164 10-year decline from year 20 to year 30, and gene expression levels (highest quartile divided into tw

165 tied to multiple metabolic processes on the gene expression level in a diverse range of cancer cell

166 east three possible scenarios: (a) The total gene expression level in a polyploid is similar to that

167 ommonly altered at both gene copy number and gene expression level in cancer cells.

168 th early-onset bipolar disorder and a higher gene expression level in human prefrontal cortex.

169 clein induces more pronounced changes at the gene expression level in mouse primary dopamine (DA) neu

170 this pilot study assessed whether the alpha7 gene expression level in septic patients' peripheral blo

171 ning the epigenetic effect of the changes in gene expression level in the F1 hybrids showed that the

172 rong similarity between sJIA and CAPS at the gene expression level in which several genes that form a

173 he genotype combinations of the two SNPs and gene expression levels in 13 areas of human central nerv

174 iduals of European ancestry and investigated gene expression levels in 7,773 samples.

175 s by correlating genotype with RNA-seq-based gene expression levels in 96 human kidney samples.

176 we examined the associations between SES and gene expression levels in adulthood, with particular foc

177 strate significant variations in isoform and gene expression levels in anatomically different muscles

178 hment of functional variants associated with gene expression levels in brain regions.

179 NA-seq) is a powerful approach for measuring gene expression levels in cells and tissues, but it reli

180 een well documented, the genetic patterns of gene expression levels in chickens remain to be determin

181 mplex, and comparison of chromatin marks and gene expression levels in control and REST-deficient ste

182 ity is differentially recruited to fine-tune gene expression levels in each cardiac chamber.

183 ng the periimplantation period determined by gene expression levels in extraembryonic tissues and the

184 th scRNA-seq to measure cell cycle phase and gene expression levels in human induced pluripotent stem

185 Human gene expression levels in humanized mouse livers were an

186 We measured gene expression levels in infected and non-infected cell

187 of disease susceptibility, we characterized gene expression levels in iPSC-CMs in humans and chimpan

188 we report on a method for precise control of gene expression levels in mammalian cells using engineer

189 have recently been developed for controlling gene expression levels in mammalian cells, but most have

190 dings indicate that variants which influence gene expression levels in multiple tissues are more like

191 ack and feedforward circuits that fine-tuned gene expression levels in response to DNA damage to perm

192 ble to respond to exogenous auxin and AtDRO1 gene expression levels in root tips were unaffected by t

193 uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populati

194 erved across species; associated with strong gene expression levels in testes; and overrepresented on

195 rprising power to detect, genetic effects on gene expression levels in the baboons.

196 Lastly, we trained a classifier based on the gene expression levels in the non-infected cells, and de

197 Consequently, it is now possible to study gene expression levels in thousands of cells from the sa

198 Higher gene expression levels in TLR5 and CCR1 are associated w

199 A binding specificities and predicts precise gene expression levels in varying cellular contexts.

200 ve greatly increased our ability to identify gene expression levels, including at specific developmen

201 ological organization, higher liver-specific gene expression levels, increased metabolic product secr

202 This study reveals that the PBMC alpha7 gene expression level is a clinically relevant marker fo

203 rmation can be faithfully transmitted to the gene expression level is unclear.

204 Although precise tuning of gene expression levels is critical for most developmenta

205 Evolutionary constraint in gene expression levels is not reflected in the conservat

206 nce between condition-specific variances) of gene expression levels is simply neglected or calibrated

207 Although several SCNAs are known to change gene expression levels, it is not clear whether each ind

208 ations are generally correlated with overall gene expression levels, it remains unclear how histone m

209 leotide polymorphisms (SNPs) associated with gene expression levels, known as expression quantitative

210 that the encoded protein shape together with gene expression level largely determines the resulting p

211 tered gene expression and that parameters of gene expression-levels, location, and state-were convolv

212 Therefore, measuring host gene expression levels may be beneficial for the diagnos

213 taset of somatic copy-number alterations and gene expression levels measured in glioblastoma samples

214 In a cohort of 846 individuals with 7,339 gene expression levels measured in peripheral blood, we

215 Gene expression levels measured with full transcript len

216 ns unclear whether this overlap is driven by gene expression levels 'mediating' genetic effects on di

217 ion response to WD also was reflected in the gene expression levels (most notably those of NDL1, CHAL

218 r example, the relative rather than absolute gene expression level needs to be considered, requiring

219 Cell-to-cell variation in gene expression levels (noise) generates phenotypic dive

220 approach to filter interaction data based on gene expression levels normalized across tissues or deve

221 Additionally, gene expression level of anti-apoptotic genes BCL2 and B

222 ta, IL-6, and IL-8) across stimuli, a higher gene expression level of TLR2 (P = .02) and TLR9 (P = .0

223 In the validation phase, the gene expression levels of ALPL in leukocytes were signif

224 -genotypes exhibited distinct differences in gene expression levels of capsule and attachment genes c

225 Gene expression levels of CLCA1 and periostin, but not S

226 Gene expression levels of HLA-DRA were an independent ma

227 t N=51 women using first trimester antenatal gene expression levels of HP1BP3 and TTC9B, with an area

228 was isolated from the paraffin material, and gene expression levels of IL-32 alpha, beta, and gamma i

229 Strikingly, the gene expression levels of inflammatory monocytes dramati

230 ses also revealed significant alterations in gene expression levels of key enzymatic regulators of bi

231 pression in NCI-H2452 and NCI-H2052, whereas gene expression levels of MT1A and MT1B were low or abse

232 ndividuals, potentially through an effect on gene expression levels of MYOZ1.

233 Gene expression levels of P. falciparum invasion ligands

234 Gene expression levels of soluble RANKL, osteoprotegerin

235 ng markers for immunologic unresponsiveness, gene expression levels of TCL1A and CD79B may also ident

236 Moreover, we found that the gene expression levels of the NLRP3-related proteins NLR

237 In the validation phase, gene expression levels of the promising genes from the O

238 The gene expression levels of the receptor were evaluated by

239 In addition to IL-27, gene expression levels of the specific IL-27 receptor (I

240 Moreover, the gene expression levels of the three susceptible loci wer

241 fferent growth conditions, bringing together gene expression levels of the triacylglycerol biosynthes

242 ive was to study the association between the gene expression levels of these six genes and lung funct

243 DNA methylation levels in atrophic Sol, the gene expression levels of total nNOS and nNOSu (i.e. the

244 rophy, 12 h of cast immobilization decreased gene expression levels of total nNOS and nNOSu in Sol.

245 itamin D in hPDLCs was assessed based on the gene expression levels of vitamin D receptor (VDR)-regul

246 Gene-expression levels of 119 genes were associated with

247 Our results implicate a threshold effect of gene expression level on photoreceptor function and surv

248 s for pathway analyses focus on representing gene expression levels on graph representations of pathw

249 n amplitude are due to individual changes in gene expression level or to a change in coherence of the

250 hput biological assays, measurements such as gene expression levels or protein phosphorylation intens

251 dividual cells to fluctuate substantially in gene expression levels over time.

252 oth at the DNA copy number (P<0.001) and RNA gene expression level (P<0.001).

253 Genetic variants that modulate gene expression levels play an important role in the eti

254 This work demonstrates that elevated gene expression levels, proposed to be associated with A

255 s starting from raw paired-end RNA-seq data: gene expression levels, quality metrics, detection of un

256 different AML mouse models with reduced GFI1 gene expression levels revealed a direct link between lo

257 that regulates complex traits, metabolites, gene expression levels, RNA editing levels and DNA methy

258 tion of the magnitude of DE, distribution of gene expression level, sequencing coverage and the choic

259 iation together with histone methylation and gene expression levels showed that histoneQTLs are an im

260 On the gene expression level, strategies are presented that mak

261 kles is more deterministic and predictive of gene expression levels than gene radial positioning.

262 ress and strain structures within cells into gene expression levels that impact development, homeosta

263 attacks and a specific attack using outlier gene expression levels that is simple yet accurate.

264 CS produces significant changes in offspring gene expression levels that supersede age-related and ge

265 lex organs but also the evolution of overall gene expression levels that underlie them.

266 ntitative mapping from promoter sequences to gene-expression levels that is compatible with in vivo a

267 isease models to edit genomes and to control gene expression levels through CRISPR interference (CRIS

268 differences in both dominant and minor vlhA gene expression levels throughout the first week of infe

269 sulators, subsequently changing their target gene expression levels to achieve therapeutic benefits -

270 e a correlation between gene copy number and gene expression level (transcript abundance), but this h

271 Introns can increase gene expression levels using a variety of mechanisms col

272 tween polymorphic TE (polyTE) loci and human gene expression levels using an expression quantitative

273 these decisions include (1) how to integrate gene expression levels using gene-protein-reaction rules

274 to mitigate the dropout problem by imputing gene expression levels using information from other cell

275 ional changes affecting steady-state overall gene expression levels using microarray based approaches

276 erall conclusion that step-wise control over gene expression levels using the miSFIT constructs remai

277 Gene expression levels vary greatly within similar cells

278 We validated gene expression levels via RT-qPCR and microRNA target v

279 The reporter gene expression level was confirmed via immunoblotting,

280 pression peak was observed at day 2, and the gene expression level was up to 5-fold higher than that

281 ighted summary expression score of the seven gene expression levels was computed.

282 ession ratio; and ID1, BAALC, ERG, and KMT2E gene expression levels, we modeled ISAPL in 159 patients

283 Standardized gene expression levels were analyzed relative to enumera

284 Relative gene expression levels were estimated by quantitative re

285 Gene expression levels were evaluated by real-time PCR.

286 In this prospective single-center study, gene expression levels were evaluated using real-time Ta

287 Gene expression levels were investigated in relation to

288 esting was used to measure lung function and gene expression levels were measured using the Nanostrin

289 ical cows, whereas increased IL-10 and IL-17 gene expression levels were observed for both infection

290 Gene expression levels were opposite to methylation stat

291 We found that all marker gene expression levels were significantly elevated in th

292 D group and 18 hr in the DBD and DCD groups, gene expression levels were similar to those found after

293 Gene expression levels were strongly associated with cel

294 UBR5 was hypomethylated and increased at the gene expression level, whereas a suppression of MuRF1/MA

295 macrophages had the highest pro-inflammatory gene expression levels, while large alveolar macrophages

296 t this system can be used to control in vivo gene expression levels with low background, large dynami

297 cific effects by antipsychotic medication on gene expression levels with scant overlap of genes diffe

298 ite measurements to recover high-dimensional gene expression levels (with 100 times fewer measurement

299 Increased pausing has a non-linear effect on gene expression levels, with moderately paused genes bei

300 biological sciences by revealing genome-wide gene expression levels within individual cells.