ライフサイエンスコーパス: gene regulatory network

1 ing networks in biology (e.g., signaling and gene regulatory networks).

2 es has made it difficult to decipher the p63 gene regulatory network.

3 ir mRNA profiles provides insight into their gene regulatory network.

4 poptosis of cancer cells occurs by a complex gene regulatory network.

5 t produce attractor states in the underlying gene regulatory network.

6 of stochastic fluctuations can depend on the gene regulatory network.

7 allmark of the criticality of the underlying gene regulatory network.

8 tion patterns was associated with a distinct gene regulatory network.

9 captured in a chronological model of the JA gene regulatory network.

10 genome and are directly associated with the gene regulatory network.

11 study, we first construct a cell fate miRNA-gene regulatory network.

12 t produce attractor states in the underlying gene regulatory network.

13 ve genes and highly overlaps with the ARID1A gene regulatory network.

14 malies, and these are regulated by a complex gene regulatory network.

15 in part from cooption of fluctuations in the gene regulatory network.

16 ure only observed before in a toy model of a gene-regulatory network.

17 n of BAP1 in the regulation of the ER stress gene-regulatory network.

18 tural selection on environmentally sensitive gene regulatory networks.

19 ntogeny is accompanied by dynamic changes in gene regulatory networks.

20 olution to generate new functions and rewire gene regulatory networks.

21 on of specific retinal fates and alternative gene regulatory networks.

22 ession is an important step in understanding gene regulatory networks.

23 entities are generated by reconfiguration of gene regulatory networks.

24 confidence metrics using realistic in silico gene regulatory networks.

25 ther food legumes indicating the presence of gene regulatory networks.

26 s (TEs) are thought to have helped establish gene regulatory networks.

27 operties can be readily related to the miRNA gene regulatory networks.

28 help us relate the structure and function of gene regulatory networks.

29 on can illuminate components of TF-dependent gene regulatory networks.

30 del in describing the behaviour of stem cell gene regulatory networks.

31 and tissue organization, and the underlying gene regulatory networks.

32 s, protein-protein interaction networks, and gene regulatory networks.

33 orks have been used successfully in modeling gene regulatory networks.

34 mplexity of biological systems is encoded in gene regulatory networks.

35 our progress to further our understanding of gene regulatory networks.

36 and computational framework for deciphering gene regulatory networks.

37 s for quantitatively integrating miRNAs into gene-regulatory networks.

38 sms for eons have catalysed the evolution of gene-regulatory networks.

39 nomic events, including the evolution of new gene-regulatory networks(1,2), the de novo evolution of

40 Whereas conservation of gene regulatory networks across higher taxa supports gen

41 lticellular and unicellular regions of human gene regulatory networks activate primitive transcriptio

42 To understand variation in gene regulatory networks activated by submergence, we co

43 transcription factors and chromatin dictates gene regulatory network activity.

44 Disruption of the fast VCS gene regulatory network allowed nodal physiology to emer

45 tomated 'gene expression as a phenotype' and gene regulatory network analyses.

46 Gene regulatory network analysis indicated that a comple

47 A gene regulatory network analysis showed that many of the

48 a computationally-inferred context-specific gene regulatory network and applies topological, statist

49 that NeTFactor's results are robust when the gene regulatory network and biomarker are derived from i

50 e Notch pathway, it entails a complex set of gene regulatory network and chromatin state changes even

51 This review focuses on the gene regulatory network and chromatin-based kinetic cons

52 further constructed a cardiac reprogramming gene regulatory network and found repression of EGFR sig

53 largely relies on uncovering the complicated gene regulatory network and further characterization of

54 on the computed probabilistic landscape of a gene regulatory network and of a toggle-switch network.

55 We devise a disease-specific enhancer-gene regulatory network and predict that primed enhancer

56 tor subunits at the core of the pluripotency gene regulatory network and will enhance our ability to

57 amework's applicability in dynamic models of gene regulatory networks and identify nodes whose overri

58 using Esrp1 mutant disease models to examine gene regulatory networks and pathways that are essential

59 these new tools could be used to investigate gene regulatory networks and their control mechanisms.

60 sionary contribution to our understanding of gene regulatory networks and their evolution is acknowle

61 We exemplify the symmetry fibrations in gene regulatory networks and then show that they univers

62 ondly, EPEE incorporates context-specific TF-gene regulatory networks and therefore adapts the analys

63 Gene regulatory networks and tissue morphogenetic events

64 e studies also provide new insights into the gene regulatory networks and/or dynamic cellular process

65 should be useful for rationally engineering gene-regulatory networks and for studying the biophysics

66 vides insight into a previously unrecognized gene regulatory network, and demonstrates how cross-regu

67 yze module-based network approaches to build gene regulatory networks, and compare their performance

68 In summary, our conserved miRNA-TF-gene regulatory network approach is effective in detecti

69 Gene regulatory networks are composed of sub-networks th

70 he extent to which cell- and tissue-specific gene regulatory networks are established.

71 Gene regulatory networks are largely responsible for cel

72 firm that commonly used stochastic models of gene regulatory networks are only accurate in a subset o

73 Precisely controlled gene regulatory networks are required during embryonic d

74 We propose that gene regulatory networks are sufficiently interconnected

75 Gene regulatory networks are typically constructed from

76 rtantly, we demonstrate that these synthetic gene-regulatory networks are functional in an influenza

77 tin profiling identifies how cell states and gene-regulatory networks are modulated by stretching.

78 Gene-regulatory networks are ubiquitous in nature and cr

79 We show that logic computational circuits in gene regulatory networks arise from a fibration symmetry

80 eractomes, chromatin interaction network and gene regulatory network, as a proof of principle to iden

81 Data Assimilations (PANDA) to construct the gene regulatory networks associated with good responders

82 ls possess distinct chromatin landscapes and gene regulatory networks associated with tumorigenesis a

83 al for CRISPR screens to map and interrogate gene regulatory networks at unprecedented speed and scal

84 is (TimeReg) as a method for the analysis of gene regulatory networks based on paired gene expression

85 ersuaded to dig out intrinsic mechanisms and gene regulatory networks behind DB infestation to date p

86 ted time-series data covering many different gene regulatory networks, BINGO clearly and consistently

87 equation models have also been used to model gene regulatory networks, but these frameworks tend to b

88 es have indicated these eRNAs play a role in gene regulatory networks by controlling promoter and enh

89 of these steroid-producing immune cells and gene regulatory networks by using single-cell transcript

90 and differentiated cell behavior, and that a gene regulatory network can be rapidly assembled to rein

91 er these findings provide insight into how a gene regulatory network can coopt variation intrinsic to

92 Gene regulatory networks can be modelled in various ways

93 complex probability landscape of stochastic gene regulatory networks can further biologists' underst

94 The rewiring of gene regulatory networks can generate phenotypic novelty

95 We found that the topologies of adaptive gene regulatory networks can still be grouped into two g

96 As a layer of the gene regulatory network, circRNA expression is also an i

97 However, the gene-regulatory network components that are functionally

98 multitask learning and constructed a global gene regulatory network comprising 12,228 interactions.

99 Much progress has been made in deciphering gene regulatory networks computationally.

100 Inspired by nature, where gene regulatory networks consisting of intercommunicatin

101 seases hierarchies and heterogeneity, causal gene regulatory network construction, and drug developme

102 fficient and easy-to-use web application for gene regulatory network construction.

103 Gene regulatory networks control development via domain-

104 Gene regulatory networks control tissue homeostasis and

105 complex-specific functions by perturbing the gene regulatory network controlled by a single complex.

106 les, this study identifies a key step in the gene regulatory network controlling leaf growth in respo

107 ation of these four TFs and PHO1;H3 in a new gene regulatory network controlling phosphate accumulati

108 nding promoters, which we then used to build gene-regulatory networks de novo.

109 Gene regulatory networks describe the regulatory relatio

110 ed and utilized to generate a salivary gland gene regulatory network describing the genome-wide chrom

111 rm in the urochordate Ciona, where a related gene regulatory network determines cardiac or skeletal m

112 tions to Notch1a and Emx2, we infer that the gene-regulatory network determining cell polarity includ

113 es; therefore, the reconstruction of dynamic gene regulatory networks (DGRNs) is an important but dif

114 A high versus low cells express differential gene regulatory networks, differential sensitivity to th

115 Key components of the photosynthesis gene regulatory network differentially accumulated betwe

116 jority of the initially proposed methods for gene regulatory network discovery create a network of ge

117 ess, we propose a novel approach to estimate gene regulatory networks drawing from the module-based m

118 e gene-flavonoid association and rebuilt the gene regulatory network during macrosclereid cell develo

119 and uncovered the dose-dependent rewiring of gene regulatory network during mating differentiation.

120 Mapping the gene-regulatory networks dysregulated in human disease w

121 indings reveal how changes in the underlying gene regulatory network facilitate eye size evolution an

122 A hypothesized gene regulatory network for N was proposed.

123 this approach allowed the construction of a gene regulatory network for whole-body regeneration, ena

124 ructing novel and comprehensive genome-scale gene regulatory networks for various organisms.

125 e study empirical mutualistic networks and a gene regulatory network, for which the nonlinear nodal i

126 to extract the topological information of a gene regulatory network from single-cell gene expression

127 Inferring gene regulatory networks from gene expression time serie

128 We benchmarked a framework for learning gene regulatory networks from scRNAseq data that incorpo

129 of state-of-the-art algorithms for inferring gene regulatory networks from single-cell transcriptiona

130 Reverse engineering of gene regulatory networks from time series gene-expressio

131 these myogenic progenitors, where different gene regulatory networks function, with T-box factor 1 (

132 tal brain and organoids have helped identify gene regulatory networks functioning at early stages of

133 These new insights into EpiSC gene regulatory networks gained from this study are high

134 Gene regulatory networks govern the function of key cell

135 In an A. thaliana developmental gene regulatory network, GRACE recovers cell cycle relat

136 tal goal in biology, but connections between gene regulatory network (GRN) activity and individual di

137 g protocols has enabled the study of the p53 gene regulatory network (GRN) and underlying mechanisms

138 gulation of the anterior neuroectoderm (ANE) gene regulatory network (GRN) by canonical Wnt/beta-cate

139 A gene regulatory network (GRN) controls the specification

140 we built the first computationally predicted gene regulatory network (GRN) for molluscan biomineraliz

141 t disease (CHD); however, the underlying CHD gene regulatory network (GRN) imbalances are unknown.

142 The gene regulatory network (GRN) of human cells encodes mec

143 The gene regulatory network (GRN) of naive mouse embryonic s

144 However, the gene regulatory network (GRN) orchestrating the early sp

145 Downstream gene regulatory network (GRN) reconstruction was found t

146 of 51,199 mouse cells of ectodermal origin, gene regulatory network (GRN) screens in conjunction wit

147 alable algorithm for identifying genome-wide gene regulatory network (GRN) structures, and we have ve

148 y work has been carried out to determine the gene regulatory network (GRN) that results in plant cell

149 that stress pathways interact with the auxin gene regulatory network (GRN) through transcription of t

150 model of combined epigenetic regulation (ER)-gene regulatory network (GRN) to study the plastic pheno

151 ining in silico modelling of a reconstructed gene regulatory network (GRN) with in vitro validation o

152 sion of the NF-kappaB-dependent inflammatory gene regulatory network (GRN), including the IFN respons

153 or such states and decipher their underlying gene regulatory network (GRN), we studied 10 melanoma cu

154 yer of networked activities in the brain-the gene regulatory network (GRN)-that orchestrates expressi

155 n insight into the ancestral state of the NC gene regulatory network (GRN).

156 to test the biological significance of these gene regulatory networks (GRN).

157 Reconstructing gene regulatory networks (GRNs) based on gene expression

158 ystematic approach that reconstructs altered gene regulatory networks (GRNs) by combining enhancer me

159 ed perturbations collectively disrupt normal gene regulatory networks (GRNs) by increasing their entr

160 ng these unique programs, archaeal cells use gene regulatory networks (GRNs) composed of transcriptio

161 To understand the gene regulatory networks (GRNs) driving this phase of he

162 Dynamic reprogramming of gene regulatory networks (GRNs) enables organisms to rap

163 Animal behavior is ultimately the product of gene regulatory networks (GRNs) for brain development an

164 The inference of gene regulatory networks (GRNs) from DNA microarray meas

165 Reconstructing gene regulatory networks (GRNs) from expression data pla

166 Predicting gene regulatory networks (GRNs) from expression profiles

167 Reconstruction of gene regulatory networks (GRNs) from gene expression pro

168 The heritability contribution of gene regulatory networks (GRNs) in CAD, which are modula

169 ades, biologists have shown that cooption of gene regulatory networks (GRNs) indeed underlies numerou

170 Gene regulatory networks (GRNs) link transcription facto

171 Developmental gene regulatory networks (GRNs) must therefore synchroni

172 Gene regulatory networks (GRNs) of the same organism can

173 Analyses of gene regulatory networks (GRNs) provide the ability to u

174 In Xenopus, we have been studying the gene regulatory networks (GRNs) required for the formati

175 n arises from changes to the topology of the gene regulatory networks (GRNs) that control the highly

176 Gene regulatory networks (GRNs) that direct animal embry

177 Lineage specification is governed by gene regulatory networks (GRNs) that integrate the activ

178 The reconstruction of gene regulatory networks (GRNs) using single cell transc

179 The DryNetMC does not only infer gene regulatory networks (GRNs) via an integrated approa

180 Furthermore, analyses of gene regulatory networks (GRNs) yielded master regulator

181 TFs and their target genes are organized in gene regulatory networks (GRNs), and thus uncovering GRN

182 Disruptions in gene regulatory networks (GRNs), driven by multiple dele

183 sses is encoded in the genome in the form of gene regulatory networks (GRNs).

184 rgetic landscapes associated with underlying gene regulatory networks (GRNs).

185 ellular and multicellular genes within human gene regulatory networks (GRNs).

186 ment arise from evolutionary modification of gene regulatory networks (GRNs).

187 changes that have restructured developmental gene regulatory networks (GRNs).

188 e opportunity to understand the evolution of gene regulatory networks (GRNs).

189 es of linear regulatory chains (LRCs) within gene regulatory networks (GRNs).

190 y modules (CRMs) working together in sets of gene regulatory networks (GRNs).

191 tomics, and advances in our understanding of gene regulatory networks have enhanced our perspective o

192 mplex dynamics-from inorganic oscillators to gene regulatory networks-have been long known but either

193 binatorial regulation is a common feature in gene regulatory networks, how it evolves and affects net

194 Analysis of the DNase1 gene regulatory network identified dense interconnectivi

195 data from GWAS to functional pathways from a gene regulatory network identified known genes with high

196 atin states in development may constrain how gene regulatory networks impart embryonic pattern.

197 As the main application, we analyzed the gene regulatory network in lung adenocarcinoma, finding

198 to low temperature, and activates a complex gene regulatory network in response to cold stress.

199 en on identifying its direct targets and the gene regulatory network in which it operates.

200 hundreds of genes, giving rise to a complex gene regulatory network in which transcripts carrying mi

201 mutational hotspots that potentially disrupt gene regulatory networks in cancer.

202 differences of gene expression networks and gene regulatory networks in children who develop asthma

203 rturb-ATAC is a powerful strategy to dissect gene regulatory networks in development and disease.

204 or valvular interstitial cells; inference of gene regulatory networks in valvular interstitial cells

205 A detailed understanding of the gene-regulatory network in ankylosing spondylitis (AS) i

206 e and biological levels of organization; and gene-regulatory networks in behavior and development and

207 e identification and function of AF-relevant gene regulatory networks, including variant regulatory e

208 ion, we developed an algorithm called GRACE (Gene Regulatory network inference ACcuracy Enhancement).

209 BEELINE will aid the development of gene regulatory network inference algorithms.

210 To improve the accuracy of gene regulatory network inference and facilitate candida

211 d ease of use, even by non-specialists, make gene regulatory network inference available to any resea

212 However, gene regulatory network inference for most eukaryotic or

213 We used gene regulatory network inference, genetic interaction a

214 our data demonstrate that ARX functions in a gene regulatory network integrating normal forebrain pat

215 tomes and to provide a blueprint to identify gene regulatory network involved in a given biological p

216 ctuations and the topology of the underlying gene regulatory network is of fundamental importance for

217 Constructing gene regulatory networks is crucial to unraveling the ge

218 vs divergence in the configuration of these gene regulatory networks is less clear.

219 The major obstacle in inferring gene regulatory networks is the lack of data.

220 To fully understand gene regulatory networks, it is therefore critical to ac

221 ANCER OF TRY AND CPC1 This modulation of the gene regulatory network leads to altered levels and dist

222 A gene regulatory network links transcription factors to t

223 by establishing a multilayered hierarchical gene regulatory network (ML-hGRN) centered around a give

224 A multilayered hierarchical gene regulatory network (ML-hGRN) mediated by PuHox52 wa

225 Testing on the newly designed single-cell gene regulatory network model and applying to twelve pub

226 Using gene regulatory network modeling, we identified candidat

227 Using gene regulatory network models, we compared transcriptio

228 differentiation is exerted through specific gene regulatory network motifs.

229 ics for several protein-folding transitions, gene-regulatory network motifs, and HIV evolution pathwa

230 Furthermore, we establish the first gene regulatory network of cell fate commitment that int

231 key transcription factor of the endomesoderm gene regulatory network of embryos in the sea urchin, is

232 ed the differential connectivity between the gene regulatory network of good responders versus that o

233 tion factor, a key regulator of the anterior gene regulatory network of insects.

234 age, by additional changes to the downstream gene regulatory network of transcription factors, giving

235 ocess of self-organization that emerges from gene regulatory networks of differentiating stem cells.

236 A deeper mechanistic understanding of the gene regulatory networks of regeneration pathways might

237 Knowing transcriptional profiles and gene regulatory networks of SV cell types establishes a

238 expression, providing evidence of a putative gene regulatory network operating in flight feather patt

239 iled studies pertaining to the metabolic and gene regulatory networks operating in the glandular tric

240 s on interconnected signaling, metabolic and gene regulatory network pathways represented in standard

241 ur work illuminates the complexity of the JA gene regulatory network, pinpoints and validates previou

242 The role promoter-associated gene-regulatory-networks play in development-associated

243 Through gene regulatory network reconstruction, we found that Hi

244 abolic differences, organoid models preserve gene regulatory networks related to primary cell types a

245 ting other essential TF(s) of the glyceollin gene regulatory network remain to be identified.

246 though we know a lot about the signaling and gene-regulatory networks required for this process, much

247 lators of AS are essential components of the gene regulatory network, required for normal cellular fu

248 Deciphering gene regulatory networks requires identification of gene

249 o function independently of the known SPE-44 gene regulatory network, revealing the existence of an N

250 l regulation allows for rapid expansion of a gene regulatory network's targets, possibly extending it

251 e experimentally demonstrated how underlying gene regulatory networks shape the landscape and hence o

252 Gene regulatory networks show the deep homology of scale

253 For instance, a conserved anterior gene regulatory network specifies the ancestral neuroend

254 d feed-forward loop) are classic features of gene regulatory networks specifying cell fates.

255 ion factor AP-2 alpha (tfap2a) coordinates a gene regulatory network that activates the terminal diff

256 similar single-cell profiles, and generate a gene regulatory network that both recovers known interac

257 namic changes in gene expression(1), but the gene regulatory network that controls oocyte growth rema

258 Alx1 is a pivotal transcription factor in a gene regulatory network that controls skeletogenesis thr

259 Our work uncovers components of a gene regulatory network that controls the initial specif

260 of downstream transcriptional factors in the gene regulatory network that establishes root epidermal

261 Therefore, we constructed a gene regulatory network that identifies the set of bZIPs

262 We describe a conserved, likely ancient, gene regulatory network that intriguingly operates conte

263 The failures in the gene regulatory network that lead to cancer are abstract

264 at Lin28b and Igf2bp3 are at the center of a gene regulatory network that mediates the fetal-adult he

265 We argue that the gene regulatory network that patterns segments may be re

266 ns anchor cell invasion, we characterize the gene regulatory network that promotes cell invasion.

267 at digit tip regeneration is controlled by a gene regulatory network that recapitulates aspects of li

268 of the transcriptional control mechanism of gene regulatory networks that act in the same processes

269 that alter the form or function of molecular gene regulatory networks that are then filtered by natur

270 Although gene regulatory networks that control skeletal muscle at

271 as posed a major obstacle to identifying the gene regulatory networks that control these processes.

272 To understand the gene regulatory networks that control this differentiati

273 yses provide a more complete overview of the gene regulatory networks that define this cell type, and

274 l control to major signalling components and gene regulatory networks that diversifies gene expressio

275 s data and to build predictive models of the gene regulatory networks that drive the sequence of cell

276 s completely ignore the topological order of gene regulatory networks that hold key characteristics i

277 The complexity of gene regulatory networks that lead multipotent cells to

278 ribed in breast cancer cells direct critical gene regulatory networks that promote pathogenesis.

279 To identify gene regulatory networks that reprogram Muller glia into

280 ional consequences of noncoding variation in gene regulatory networks that stabilize pluripotent stat

281 to morphogen gradients acting upstream of a gene regulatory network, the architecture of which deter

282 hese opportunities by gleaning insights into gene regulatory networks through the analysis of gene as

283 the expression of therapeutically important gene regulatory networks through the recruitment of tran

284 thematical model that connects the flagellar gene regulatory network to flagellar construction.

285 e sea urchin embryo for its well-established gene regulatory network to interrogate the embryo using

286 nscription factors that are likely to form a gene regulatory network to orchestrate fate specificatio

287 pproaches appear as possible alternatives to gene regulatory networks to understand development.

288 litates the dissection of complex changes in gene regulatory networks triggered by miRNAs and identif

289 chick embryo, we uncover novel genes in the gene regulatory network underlying otic commitment and r

290 Equally ill-defined is the gene regulatory network underlying the progression of su

291 thereby identified the genetic cascades and gene regulatory networks underlying the progression of t

292 This analysis identified several aspects of gene-regulatory networks underlying human MGE specificat

293 st, Saccharomyces cerevisiae, we constructed gene regulatory networks using a two-stage penalized lea

294 Reverse engineering approaches to infer gene regulatory networks using computational methods are

295 ogical systems, while offering insights into gene regulatory networks via synexpression analysis.

296 tion of transcription factors in time in the gene regulatory network was implicated.

297 rchitecture and dynamic regulation of the JA gene regulatory network, we performed a high-resolution

298 ata generated from artificial and real-world gene regulatory networks, we show that our algorithm can

299 y into the myogenic program is controlled by gene regulatory networks, where paired box gene 3 (Pax3)

300 Finally, we identify homeostatic gene regulatory networks within spindle and root cells,