ライフサイエンスコーパス: network

1 etal control network and the fronto-temporal network.

2 important component to the nitrate signaling network.

3 nectivity favors cooperation in a biological network.

4 /+) but not the Fbxl3(Afh/Afh) vSCN neuronal network.

5 f their location and influence in the social network.

6 illary retina revealed a dense microvascular network.

7 orks, and have assumed a completely censused network.

8 f reactions used to fill gaps in a metabolic network.

9 d with the 'default mode' or 'task negative' network.

10 enzymatic reactions in the tomato metabolic network.

11 axel or nocodazole due to changes in the MTs network.

12 ugh a specialized GA-independent trafficking network.

13 nsic connectivity within the medial amygdala network.

14 es KIT signaling cascade through Sp1/miR-29b network.

15 regulatory role in defined modules of the JA network.

16 cture of RNA is constrained using an elastic network.

17 1 mRNA, a core component of the pluripotency network.

18 ctivity between hubs of the reading/language networks.

19 14.63) and executive (MD = 21.00) attention networks.

20 e populations of synapses that compose those networks.

21 ional specialization of hippocampal-cortical networks.

22 d through comparative analysis of biological networks.

23 molecular sieving gels in PDMS microchannel networks.

24 p (21.19 mm(-1) vs. 24.38 mm(-1); P < 0.001) networks.

25 derlying structural connectivity in neuronal networks.

26 engineered binding proteins and interaction networks.

27 s well as the E2F2 and FOXM1 transcriptional networks.

28 rk degree distribution in large ultra sparse networks.

29 e easily extended to the analysis of massive networks.

30 dered state to another in real and synthetic networks.

31 he structure and function of gene regulatory networks.

32 technology with up-scaled memristive neural networks.

33 HIV prevention trials (HIV Prevention Trials Network 039 and Partners in Prevention HSV/HIV Transmiss

34 As insurance networks, accountable care organizations, and alternativ

35 the evolution of the diversity of biological networks across plants and animals and (ii) can be used

36 pendent momentum filters, whereas triangular networks act as stabilizing elements.

37 sylation as a potential hub of the signaling network affecting multiple aspects of metabolic alterati

38 ate the alignment scoring schemes and global network aligners on large scale PPI data and observe tha

39 the CUFID framework and extend it for local network alignment, specifically to solve network queryin

40 Network analyses demonstrated that 51 traits could be li

41 f SAOMs in appropriate systems, with dynamic network analyses likely to prove highly informative.

42 ile differential expression and coexpression network analyses revealed transcriptional profiles of in

43 ated for COPD in Weighted Gene Co-Expression Network Analysis (WGCNA) was enriched for B cell pathway

44 Proximity labeling and protein interaction network analysis reveal that CPH1 functions as a hub lin

45 Bayesian network analysis revealed key driver genes within these

46 ulti-layer proteomics profiling, integrative network analysis, and functional studies define landscap

47 Upon integrated network analysis, BRCA1 and CRISP2 DMRs were identified

48 hways associated with pro-oncogenic genes at network analysis.

49 usly been applied in epidemiology and social network analysis.

50 evious research implicating the default mode network and dopaminergic dysfunction in ADHD.

51 work, where nodes represent the units of the network and edges represent connections between those un

52 s, which connect the fronto-parietal control network and the fronto-temporal network.

53 ticle spacing requires an intact microtubule network and the microtubule minus end-binding protein, P

54 re more likely to form multi-TSS interaction networks and be associated with topologically associatin

55 molecular motion, compartmentalised chemical networks and designed oscillators.

56 the electrostatic interaction between carbon networks and polymerized ionic liquids, we demonstrate t

57 ipants, we reconstructed their collaboration networks and research specializations.

58 ) strengthening functional tiered laboratory networks and systems to expand access to reliable, high-

59 tly model tissue-specific changes in pathway networks and the regulatory disruptions related to genom

60 S) for the rapid fabrication of microfluidic networks and the utility of polyacrylamide gel electroph

61 sults employ the readout of large-scale fMRI networks and, by indicating multiple functional domains

62 other architectures of CNN, Recurrent Neural Network, and Random Forest, the simple CNN architecture

63 es of link prediction have focused on social networks, and have assumed a completely censused network

64 Deep neural network approaches, which have been forwarded as computa

65 connectomics approach to understanding brain network architecture, employing advanced magnetic resona

66 troduce and experimentally realise a quantum network architecture, where the nodes are fully connecte

67 Our results shed light on the network architectures that underlie external task engage

68 ow synapses of functionally defined cortical networks are arranged within the dendrites of individual

69 However, existing methods for training these networks are either biologically implausible, and/or req

70 ch cell- and tissue-specific gene regulatory networks are established.

71 Dynamic networks are important in a number of scenarios.

72 These networks are increasingly used to inform strategies to p

73 Fracture networks are quantitatively analyzed using a combination

74 We compare our results to a network assembly model that admits tunable trophic coher

75 nd superior parietal lobule influences brain networks associated with tactually-extracted motion spee

76 Under basic conditions, the neutral network assumes radical cationic character without decom

77 Whether these network attributes exist in a regenerated microcirculati

78 oorly characterized proteins while enhancing network-based analyses of domain associations, subcellul

79 flow to the major nodes of the default mode network became more pronounced and widespread.

80 alth and Human Development Neonatal Research Network between October 2010 and January 2016.

81 the S. cerevisiae INO80 protein interaction network by isolating complexes after protein complex com

82 ults define a new component of the signaling network by which activating mutations in the FGF recepto

83 Neural networks can efficiently encode the probability distribu

84 e of networks with N-stable and (N-1)-stable network-capacity allocations by triggering cascades usin

85 L uses metabolite patterns in the incomplete network captured using a matrix factorization formulatio

86 Constitutional dynamic networks (CDNs), composed of exchangeable components tha

87 ies and edges their interdependencies, while network centrality is often a good indicator of importan

88 nterdependencies of these comorbidities, and network-clustering analysis was applied to derive diseas

89 anism by which filaments of the cytoskeletal network compete for the moving organelles to accomplish

90 ntified, quantified, and analyzed the set of network components that are vulnerable to cascading fail

91 mic model implemented on an anatomical brain network (connectome), we investigate the similarity betw

92 applied to Escherichia coli, the regulation network constructed by our proposed ESPACE method is mor

93 ntary features from multiple time-varying FC networks constructed at different levels are fused for e

94 Our model consists of individual networks constructed using molecular data generated from

95 urther, the algorithms are able to deal with networks containing different combinations of binary, ca

96 izes the need to understand how brain reward networks contribute to youth depression.

97 egulation of FOXP3/EZH2-enforced T cell gene networks contributing to the underlying intestinal infla

98 our TFs and PHO1;H3 in a new gene regulatory network controlling phosphate accumulation in zinc-depen

99 The Abl tyrosine kinase signaling network controls cell migration, epithelial organization

100 ng systems by constructing chemical reaction networks (CRNs) with well-defined dynamic properties.

101 rful technologies: deep convolutional neural networks (DCNNs) and panoramic videos of natural scenes,

102 ify estimation uncertainties in functions of network degree distribution in large ultra sparse networ

103 The structural properties of the resulting network depend on how much of the inferred connectivity

104 ATEMENT Activation of the human default mode network (DMN) can be measured with fMRI when subjects sh

105 In numerous physical models on networks, dynamics are based on interactions that exclus

106 ell as information from passive surveillance networks (e.g., citizen science) can be integrated into

107 A platform strategy will create a network effect that will benefit multiple disease progra

108 Abnormalities of the endosomal-lysosomal network (ELN) are a signature feature of Alzheimer's dis

109 any identified biclusters and co-expression networks elucidation.

110 providing information on systems rather than networks, especially information concerning prefrontal l

111 system is a hierarchically organized complex network essential for tissue fluid homeostasis, immune t

112 protocol often produced increases in global network excitability or depression of the conditioned pa

113 In a computational model of a local RT network featuring slow Cl(-) extrusion kinetics, similar

114 led to reactivate the neonatal proliferative network following infarction, which was associated with

115 work, we developed a rice gene co-expression network for anther development (RiceAntherNet) that allo

116 We included children from the Dutch National Network for Pediatric Pulmonary Hypertension.

117 paralogues can remain in the same regulatory networks for dozens of millions of years.

118 ith other macromolecules in complex cellular networks for signal transduction and biological function

119 We found that the proximal colon cancer network formed a denser network (total number of edges,

120 thods are increasingly popular for inferring networks from co-occurrence and time series data, partic

121 tions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular met

122 ed Tripartite Network (LTN), a heterogeneous network generated from biomedical linked datasets.

123 e restructured developmental gene regulatory networks (GRNs).

124 Security in wireless networks has traditionally been considered to be an issu

125 The architecture and dynamics of the FG-network have been refractory to characterization due to

126 Classification analysis of their brain network identified each of these misdiagnosed patients a

127 e the baseline climate of the protected area network in North America (Canada, United States, Mexico-

128 ional model of the cardiac mechano-signaling network in order to elucidate the mechanisms underlying

129 ntains solvent exclusion and the core H-bond network in the active site by relocating to replace the

130 However, a robust map of immune-related gene networks in circulating human cells, their interactions

131 hnique in the comparison of placental vessel networks in normal and fetal growth restriction (FGR) co

132 unctional integrity of these impacted neural networks in primary progressive aphasia are lacking.

133 The nature of signal transduction networks in the regulation of cell contractility is not

134 neurons and their hitherto unknown synaptic networks in the tadpole larva of a sibling chordate, the

135 a gestational age of 32 weeks, the adjusted network incidence of necrotising enterocolitis ranged fr

136 It relies on a widespread cortical network, including auditory sensory, but also frontal an

137 A small network incorporating neighboring insular regions and th

138 tly, the utility of SELDOM goes beyond basic network inference (i.e. uncovering static interaction ne

139 protein-protein interactions) for biological network inference.

140 ur ability to analyze and compare biological networks, inferred from experimental data, in a fast and

141 The complex networks, interactions, and responses of immune cells pr

142 sed genes was used to reconstruct regulatory networks involved in differentiation.

143 Surface reaction networks involving hydrocarbons exhibit enormous complex

144 e a scored human protein-protein interaction network (InWeb_InBioMap, or InWeb_IM) with severalfold m

145 ation of coherent light through a disordered network is accompanied by randomization and possible con

146 The structure of the competitive network is an important driver of biodiversity and coexi

147 for the first time, that the model thalamic network is capable of independently generating the susta

148 A continuous siloxane network is formed that links together the muskeg, wood f

149 ix at molecular scale to create a homogenous network is quite general and should enable development o

150 The evolution of RNA-protein regulatory networks is far less understood.

151 urces for controlling spreading processes on networks is of prime significance in diverse contexts, r

152 multilocus genotype classes in the epistatic networks is often improved by accounting for the interac

153 nstitute crucial components of epileptogenic networks, is unknown.

154 nference (i.e. uncovering static interaction networks): it builds dynamic (based on ordinary differen

155 espite the enormous complexity in biological networks, it is possible to identify network motifs that

156 To fully understand gene regulatory networks, it is therefore critical to accurately annotat

157 nctional smoothness breaks down in the later network layers.

158 oncept into an operational definition at the network level, which allows us to infer the economic wel

159 neurons are difficult to separate from their network-level actions.

160 These findings suggest that network-level alterations are present in individuals wit

161 , we sought to dissect a putative allosteric network linking a cryptic site at the dimerization inter

162 te the similarities within Linked Tripartite Network (LTN), a heterogeneous network generated from bi

163 lysis of Sey1p is inhibited, indicating that network maintenance requires continuous membrane fusion

164 Second, lesion network mapping was used to identify brain regions funct

165 However, each node in a network may be associated with many attributes.

166 lar disintegration (ie, compromised salience network membership) as a neurobiological signature of th

167 Pairwise meta-analysis and network meta-analysis were conducted.

168 A detailed comparison with the anisotropic network model (an elastic network model) highlights the

169 al patterns, we constructed a large-scale 3D network model of the granular layer.

170 gLASSO) algorithm to integrate a data-driven network model with prior biological knowledge (i.e., pro

171 th the anisotropic network model (an elastic network model) highlights the importance of flexibility

172 In recent years, several network models have been introduced to elucidate the rel

173 eering approach to infer data-driven dynamic network models of multi-organ gene regulatory influences

174 s how lncRNAs may introduce species-specific network modulations.

175 logical networks, it is possible to identify network motifs that lead to functional outputs such as b

176 , n = 173) than the distal colorectal cancer network (n = 95) (P < 0.0001 in permutation tests).

177 nown, however pathological oscillations of a network of a number of brain regions are implicated in l

178 nd physical effort was subserved by a common network of areas, including the dorsomedial and dorsolat

179 This study investigated how the cooperative network of bacteria and fungi differ between a diseased

180 for all three urban-form metrics, and with a network of buses, trams, and bicycle facilities) was tra

181 A complex hydrogen bond network of four active site residues, which was installe

182 This network of global coverage requires substantial investme

183 A network of ICUs.

184 compared our results to the national United Network of Organ Sharing database.

185 Photosynthesis begins when a network of pigment-protein complexes captures solar ener

186 cy, which is stabilized by an interconnected network of pluripotency-associated genes, integrates ext

187 tein 1 (EB1) is a key element in the complex network of protein-protein interactions at microtubule (

188 ll in traditional meta-analysis and create a network of randomized clinical trials to compare outcome

189 the body reacts to motor commands, but how a network of spiking neurons can learn non-linear body dyn

190 Using the acini-ductal network of the developing human and murine salivary glan

191 These results revealed a complex network of transcriptional regulators and pathways that

192 to rewire the endogenous cellular regulatory network of yeast to enhance compatibility with synthetic

193 lomonas spp. in three distinct co-occurrence networks of bacterial interactions revealed both common

194 The organization of magnetic ions into networks of corner-sharing tetrahedra gives rise to high

195 e analytical methods to the anatomical brain networks of human, macaque, and mouse, successfully pred

196 Although numerous studies have identified networks of interacting functional modules in the gray-m

197 ify, but once found they can point to larger networks of interactions, such as with proteins that ser

198 ivate these stabilizing mechanisms in neural networks of mature animals remain elusive.

199 uclear factor (HNF) family regulates complex networks of metabolism and organ development.

200 circuit in a marine worm reveals how simple networks of neurons can control behavior.

201 ic genes and then constructing collaborative networks of TFs but only one algorithm, called Triple-Li

202 cture derives from two independent polymeric networks - one of laminin and one of type IV collagen (F

203 , or if inhibition is particularly weak, the network operates close to an instability leading to unbo

204 o observe changes to spermathecal actomyosin network organization during cell stretch and contraction

205 restored a functional balance of gamma-band network oscillations, and allowed treated eFSE rats to e

206 TCF4 enhances NMDA receptor-dependent early network oscillations.

207 uals who ran over 350M km in a global social network over 5 years.

208 external conditions as well as to changes in network parameters arising from learning-dependent synap

209 stribution within cells, connectivity in the network, participation in supramolecular complexes, and

210 lar organization of contractile cytoskeletal networks plays a key role in force generation, while on

211 We find that species occupy highly dynamic network positions through time, causing the assembly pro

212 ivity between the sgACC and the default mode network predicted clinical improvement, as did more posi

213 the cell-cycle activator, their interaction network presents a regulatory motif characteristic of a

214 classification of data from other biological networking problems.

215 ble CATH functional families) and we use the network properties of these druggable protein families t

216 ation though incremental changes in c-di-GMP network proteins acquires knowledge from past experience

217 cal network alignment, specifically to solve network querying problems.

218 e functional connectivity of dorsal striatal networks relevant to food craving and weight gain.

219 Hybrid quantum networks rely on efficient interfacing of dissimilar qua

220 ing persistent neuronal encoding within this network remain unresolved.

221 PC subsets that contribute to separate brain networks remains unclear.

222 In this study, we show that K6a network remodeling is a host defense response that direc

223 e assembly process to be punctuated by major network reorganisations.

224 racy of the cGERGM on a testbed of simulated networks representing various commonly observed brain ar

225 FORCE trained networks reproduce behaviors comparable in complexity to

226 The obtained graphitic carbon networks show excellent electrochemical performance for

227 of connections to filter only depends on the network size according to a power-law.

228 vascular image registration method based on network structure and circuit simulation is stable, faul

229 servations can inform better measurements of network structure and our understanding of collective ph

230 acellular matrix (ECM), remodeling ECM fiber network structure by condensing, degrading, and aligning

231 The development of machine learning and network structure study provides a great chance to solve

232 loss of dopaminergic neurons, mitochondrial network structure, reduced ATP production, and flight an

233 e related to variation in multilayer contact networks structured by sex in a population of European b

234 out: in both cases, topological features of network structures influence how easily distress can spr

235 h the densely connected nature of biological networks suggests that full coverage may not be necessar

236 Using the Trauma Audit and Research Network (TARN) database, we analyzed ASDH cases in the a

237 ired both for transport from the trans-Golgi network (TGN) to the late endosome/prevacuolar compartme

238 Our studies reveal a complex molecular network that defines and restricts pluripotent developme

239 of SIMs in RC components generate a SUMO-SIM network that facilitates assembly of the RC.

240 , and RFC complex likely form an interaction network that influences the ability of poxviruses to rep

241 Our findings delineate a neural network that integrates distinct behavioral modules and

242 We define an IEC transcriptional regulatory network that is shared between fish and mammals and esta

243 We present a deep neural network that prospectively predicts lineage choice in di

244 s of a novel cytoplasmic ubiquitin-signaling network that suppresses synapse formation in the brain.

245 ations on the capsid surface and in internal networks that are responsible for EC stability.

246 e expression data from biologically relevant networks that can be user selected.

247 Neural networks that control reproduction must integrate social

248 ild predictive models of the gene regulatory networks that drive the sequence of cell fate decisions

249 Regulatory networks that include the Gata2 transcription factor pla

250 cancer cells direct critical gene regulatory networks that promote pathogenesis.

251 dition to disease-associated gene expression networks that were restored with ASO treatment, we also

252 seq analyses of NRSF targets identified gene networks that, in addition to Crh, likely contributed to

253 ar cortex (AIC), a core hub of the "salience network" that is critical for perception of interoceptiv

254 As one of the key nodes in the metabolic network, the forkhead transcription factor FOXO has been

255 ict how the resulting geometry of biological networks then governs their allometric scaling.

256 ociated mutations may perturb the regulatory network through diverse mechanisms including chromatin l

257 n in running among friends, with data on the network ties and daily exercise patterns of approximatel

258 on this success, CRACKLE II will expand the network to hospitals across the United States and Colomb

259 select nodes (sentinels, or sensors) in the network to report outbreaks.

260 and dynamically tethering the branched actin network to the WASP-family proteins that create it.

261 ion and targeted interventions in regulatory networks, to the development of mitigation policies for

262 Furthermore, we show that by varying the network topology the spike train statistics of the centr

263 es of branched organs, including their size, network topology, and spatial patterning, are encoded.

264 roximal colon cancer network formed a denser network (total number of edges, n = 173) than the distal

265 Modeling of transcriptional regulatory networks (TRNs) has been increasingly used to dissect th

266 levant to pathophysiology and the regulatory networks underlying disease.

267 have built PC gene and lincRNA co-expression networks, unraveling key biological processes where linc

268 rtainty for heterogeneous catalysis reaction networks using surrogate models that are trained on the

269 This is mainly because such networks usually engage substantial computational resour

270 The network utilized both reward modulated and non-reward mo

271 is-regulatory motif were identified from the network via the motif's enrichment or biased distributio

272 A Bayesian comorbidity network was constructed to model the interdependencies o

273 is belt, an enhanced meningitis surveillance network was established.

274 The HPM network was thus specifically implicated in the processi

275 e-scale integrated analysis of the HIF-alpha network, we identified the major protein kinase C substr

276 s execute precise actions using sparse motor networks, we imaged the activity of a complete ensemble

277 microscopy of in vitro reconstituted F-actin networks, we observed and characterized two distinct Cdc

278 Analysing more than 100 empirical networks, we show that the range of coexistence conditio

279 tronic Medical Records and Genomics (eMERGE) Network were randomly allocated to one of three hypothet

280 Social networks were assessed by asking participants to nominat

281 Weighted graph networks were then converted to circuits, in which node

282 system can be represented and analyzed as a network, where nodes represent the units of the network

283 is elastic behavior is transferable to small networks, where we found the surprising effect that line

284 in-of-function datasets reveals complex gene networks which control drug response and illustrates how

285 n the approach are the weights of the neural network, which are automatically optimized based on trai

286 at Birmingham Health System Cancer Community Network, which includes 2 academic and 10 community canc

287 ylation mechanism facilitated by an H-bonded network, which is corroborated by mutagenesis experiment

288 euron class-specific input from their target network, which is often nonreciprocal.

289 -based "autopilot role" for the default mode network, which may have important implications for our c

290 ical details about individuals in our social network, which often guide our decisions as we navigate

291 al and a signal that has traveled across the network while the system is subject to different noise l

292 Thus, CaMPARI enables network-wide, tunable, all-optical functional circuit ma

293 per exploration of the brain's vast synaptic networks will require new tools for high-throughput stru

294 a beta-cyclodextrin (beta-CD)-based polymer network with higher affinity for PFOA compared to powder

295 The integration of the gene-centered network with information derived from TF-centered approa

296 ly, we design and compare the performance of networks with N-stable and (N-1)-stable network-capacity

297 stallize to form robust open hydrogen-bonded networks with parallel indenofluorenyl cores, significan

298 economic systems can often be described by a network, with nodes representing economic entities and e

299 d for the generation of a 3D human lymphatic network within native connective tissue devoid of any ex

300 oach to generate endothelialized 3D vascular networks within cell-laden hydrogel biomaterials is intr