ライフサイエンスコーパス: metabolic network

1 ely superessential (that is, required in all metabolic networks).

2 rs, in the context of the human genome-scale metabolic network.

3 uate progress in reconstruction of the yeast metabolic network.

4 ng such enzyme promiscuity in the space of a metabolic network.

5 PK is indeed a member of the plant terpenoid metabolic network.

6 presence of a reaction in a given organism's metabolic network.

7 evaluated using Parkinson's disease-related metabolic network.

8 disorder is itself associated with a unique metabolic network.

9 s demand analyses at the level of the entire metabolic network.

10 are neighbors to a target metabolite in the metabolic network.

11 the set of reactions used to fill gaps in a metabolic network.

12 mics due to disease or a perturbation in the metabolic network.

13 rahydrofolate (THF)-mediated one-carbon (C1) metabolic network.

14 h calculation, and motif identification in a metabolic network.

15 ic network and a large-scale iAF1260 E. coli metabolic network.

16 athway behavior in the context of the entire metabolic network.

17 a substrate by a downstream neighbor in the metabolic network.

18 scuous activities of enzymes in the existing metabolic network.

19 egulatory data with an organism's genome and metabolic network.

20 predicted enzymatic reactions in the tomato metabolic network.

21 xity and the plasticity of the plant primary metabolic network.

22 the carbon and nitrogen flows in the fungal metabolic network.

23 in scale from atomistic details to an entire metabolic network.

24 bolites that anchored interconnected central metabolic networks.

25 f the Gene ontology and the KEGG database of metabolic networks.

26 athways to these compounds in large putative metabolic networks.

27 scover enzymes of previously uncharacterized metabolic networks.

28 ns that link chloroplastic and mitochondrial metabolic networks.

29 studies have also yielded novel insight into metabolic networks.

30 biochemical reactions that constitute plant metabolic networks.

31 al associations to generate richly connected metabolic networks.

32 the composition, structure and regulation of metabolic networks.

33 can be successfully applied to genome-scale metabolic networks.

34 s is thermodynamically constrained in modern metabolic networks.

35 on, both reactions that are common in extant metabolic networks.

36 ids, sugars, cofactors, and lipids in extant metabolic networks.

37 xes - of metabolic reactions in genome-scale metabolic networks.

38 e used to map and interpret dysregulation in metabolic networks.

39 latory, cofunction, protein interaction, and metabolic networks.

40 and display them in the context of relevant metabolic networks.

41 derstand the evolution of complex and robust metabolic networks.

42 s, and kinetic insulation of fluctuations in metabolic networks.

43 with an in silico systems-level analysis of metabolic networks.

44 nformation on the function and regulation of metabolic networks.

45 annotation of enzymes and the description of metabolic networks.

46 ting structural and functional properties of metabolic networks.

47 nctional predictions made with the resulting metabolic networks.

48 rate estimation of metabolic fluxes in large metabolic networks.

49 graph search to work in the context of these metabolic networks.

50 ) by employing state-of-the-art genome-scale metabolic networks.

51 ore different time-dependent ecosystem-level metabolic networks.

52 tative method for determining fluxes through metabolic networks.

53 xistence of a reaction within the organism's metabolic network; a first approximation to a genome-sca

54 s and environment by regulating gene-encoded metabolic networks according to changes in the chemistry

55 cells can concurrently decrease the elevated metabolic network activity in parkinsonian brains on an

56 bromeliads, microbial communities spanned a metabolic network adapted to oxygen-limited conditions,

57 Metabolic network alignment is a system scale comparativ

58 te that a gene-centric approach to comparing metabolic networks allows for a rapid comparison of meta

59 Both correlation studies and metabolic network analyses allowed the description of a

60 generated from an unbiased correlation-based metabolic network analysis (approach 2), and the results

61 Both approaches combine metabolic network analysis based on pseudo steady-state

62 We conclude that metabolic network analysis confirmed the validity of the

63 gorithm are tested with a small E. coli core metabolic network and a large-scale iAF1260 E. coli meta

64 ing protein 2 (SREBP2)-regulated cholesterol metabolic network and absence of bile acid repression of

65 s tend to be located at the periphery of the metabolic network and are enriched for topologically der

66 armacogenomic and clinical data with a human metabolic network and find that non-pharmacokinetic meta

67 ome-scale kinetic model of the P. aeruginosa metabolic network and gene expression profiles.

68 eview, we provide an overview of the cardiac metabolic network and highlight alterations observed in

69 r pathways in a large segment of the flavone metabolic network and provide a foundation for its furth

70 randomly delete a number of reactions from a metabolic network and rate the different algorithms on t

71 etatranscriptomic approaches to estimate the metabolic network and stimuli-induced metabolic switches

72 ve enabled the estimation of a multi-species metabolic network and the associated short-term response

73 fine-tune the balance between the endogenous metabolic network and the introduced enzymes.

74 dom forest using topological features of the metabolic network and trained on curated sets of correct

75 ve growth media for an organism based on its metabolic network and transporter complement.

76 or generating minimal nutrient sets from the metabolic network and transporters of an organism combin

77 acting pairs of organisms within a community metabolic network and whether that interaction has a pos

78 gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these

79 and genetic algorithms, a strategy to curate metabolic networks and facilitate identification of meta

80 than the antagonized strain: that is, larger metabolic networks and growth on more carbon sources.

81 d that activation of LXRalpha affected lipid metabolic networks and increased cholesterol efflux in t

82 study provides insights into OXDC-regulated metabolic networks and may provide a widely applicable s

83 t step in the reconstruction of genome scale metabolic networks and models.

84 (CoA) thioesters are ubiquitously present in metabolic networks and play a pivotal role in enzymatic

85 l fingerprints to efficiently navigate large metabolic networks and propose enzymatic connections bet

86 sly, enabled investigating the regulation of metabolic networks and proved to be useful for predictin

87 xity relies on the functional integration of metabolic networks and replicative genomes inside a lipi

88 hallenges related to the complexity of plant metabolic networks and to deficiencies in our knowledge

89 network states are compatible with a viable metabolic network, and outputs a regulatory network that

90 lites form an important layer in the complex metabolic network, and the interactions between differen

91 NetCooperate takes as input a pair of metabolic networks, and returns the pairwise metrics as

92 some key dietary and genetic factors in this metabolic network are not associated with relative perip

93 Metabolic networks are extensively regulated to facilita

94 g the transition in order to determine which metabolic networks are operational.

95 Reconstructed models of metabolic networks are widely used for studying metaboli

96 ) was proposed to determine the hot spots in metabolic networks, around which transcriptional regulat

97 L-fucose major changes in the central carbon metabolic network, as well as an increased activity of t

98 pping the global structure of the organism's metabolic network at a given instant.

99 proach for assigning reactions to incomplete metabolic networks based on a metabolite connectivity sc

100 dependence of the human red blood cell (RBC) metabolic network between 4 and 37 degrees C through abs

101 Essential metabolic networking between these compartments and thei

102 line of communication between signaling and metabolic networks, but also highlight the unusual abili

103 , to identify functional differences between metabolic networks by comparing network reconstructions

104 tes the transcriptional control of clock and metabolic networks by RORs.

105 he organisation and operation of the central metabolic network can only be addressed by analysing the

106 his work demonstrates that the topology of a metabolic network can shape kinetic parameters of enzyme

107 learners, because they require knowledge of metabolic networks, carbon transitions, and computer pro

108 functional screen identified interconnected metabolic networks centered around host energy productio

109 to similar clinical improvement and similar metabolic network changes in the CSPTC circuit, with a p

110 ye movement sleep behaviour disorder-related metabolic network characterized by increased activity in

111 y reported more complex methods that rely on metabolic network comparisons.

112 ndrial functional alterations and changes in metabolic networks connected to mitochondria following H

113 etworks using sequence homology and a global metabolic network constructed from all available organis

114 Thus, the metabolic network context and environmental conditions i

115 ions may have altered the microbiota-host co-metabolic network, contributing to the growing list of W

116 Metabolic network databases are of increasing importance

117 ous enzymes within the context of the entire metabolic network defined by the annotated metagenome.

118 and for exploring the way in which the plant metabolic network delivers specific outcomes in differen

119 Cells need to rewire their metabolic network depending on the available carbon sour

120 particular genes on or off, and that complex metabolic networks determine the levels of transcription

121 Here we show that metabolic networks differ significantly in their intrins

122 rs of evolution have yielded today's complex metabolic networks driven by efficient and highly specia

123 enables holistic insight into the microbial metabolic network driving nutrient and energy flow at ec

124 ersity on a phenotypic array probing various metabolic networks, drug resistance, and host immune cel

125 tabolic liabilities in ccRCC, whose emergent metabolic network enforces outstanding anabolic requirem

126 bolic network, we observe that these ruminal metabolic networks exhibit properties consistent with di

127 Metabolic network flux analysis (NFA) tools have proven

128 ections and challenges faced by the field of metabolic network flux phenotyping.

129 t was conducted to evaluate changes in lipid metabolic networks following a balneation exposure of ad

130 The metabolic network for sulfide assimilation and trafficki

131 We reconstructed a high-quality genome-scale metabolic network for Synechocystis sp. PCC6803 that des

132 In the web-service, we have pre-assembled metabolic networks for humans, mice, Arabidopsis and yea

133 We also observe that when applied to draft metabolic networks for multiple species, a clear negativ

134 To explore the metabolic networks for nitrogen assimilation in this bac

135 and specialized labdane-related diterpenoid metabolic network found in rice.

136 driver reactions facilitating control of 23 metabolic networks from all kingdoms of life.

137 fying the necessary condition are present in metabolic networks from diverse species, suggesting prev

138 ites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding ce

139 fficient calculation of EFMs in genome-scale metabolic networks (GSMNs) is still a challenge.

140 e, constraint-based modeling of genome-scale metabolic networks has become widely used.

141 onstraints on the predictive capabilities of metabolic networks has not been investigated in detail.

142 for the rapid reconstruction of high-quality metabolic networks has received significant attention.

143 d herein indicate that the subtleties of the metabolic network have not been captured in the current

144 The genome-scale models of metabolic networks have been broadly applied in phenotyp

145 HepatoDyn includes a large metabolic network, highly detailed kinetic laws, and is

146 entify biologically tolerable diversity of a metabolic network in an optimized culture.

147 a side-by-side comparison in a medium scale metabolic network in Escherichia Coli, we show that aCFP

148 ing regulatory mechanisms and a genome-scale metabolic network in human cell, using bile acid homeost

149 mporal and dynamic changes of the eicosanoid metabolic network in mouse bone marrow-derived macrophag

150 ll point to a reconfiguration of the central metabolic network in response to reduced availability of

151 is of the Arabidopsis (Arabidopsis thaliana) metabolic network in the chloroplast and related cellula

152 However, the role of astroglial metabolic networks in behavior is unclear.

153 on, as well as scaling properties similar to metabolic networks in biological organisms.

154 The complexity of metabolic networks in microbial communities poses an unr

155 This pattern of state specific shift in metabolic networks in MTLE may improve the understanding

156 Microbial communities (MCs) create complex metabolic networks in natural habitats and respond to en

157 vious conceptual models describing microbial metabolic networks in OMZs.

158 scuss how recent efforts delineating rewired metabolic networks in pancreatic cancer have revealed ne

159 rative resource to study transcriptional and metabolic networks in skeletal muscle in the context of

160 illustrating extensive communication between metabolic networks in the mitochondria and gene regulato

161 ein folding in mitochondria controls central metabolic networks in tumour cells, including the electr

162 l support the growth of a bacterium from the metabolic network inferred from the genome sequence of t

163 ade possible by allosteric regulation of the metabolic network, interplay between the signaling pathw

164 ems monitoring, new biomarkers discovery and metabolic network investigations.

165 Our results indicate resilience of the metabolic network irrespective of inflammation.

166 onclude that the reconstruction of the yeast metabolic network is indeed gradually improving through

167 impose a metabolic stress, in as much as the metabolic network is not forced to devote more resources

168 Understanding the control of large-scale metabolic networks is central to biology and medicine.

169 gnaling, suggesting that the organization of metabolic networks is highly conserved and that AMPK pla

170 Our understanding of individual metabolic networks is increasing as we learn more about

171 Gap filling for the reconstruction of metabolic networks is to restore the connectivity of met

172 ide insight into lignin biosynthesis and the metabolic network it is embedded in and provide a system

173 nce homology has been a standard to annotate metabolic networks it has been faulted for its lack of p

174 e to build and, because of the complexity of metabolic networks, it is hard for researchers to gain f

175 nomy can be considerably more similar at the metabolic network level.

176 olic rates) but has not been examined at the metabolic network level.

177 the metabolomics data revealed that the same metabolic network-level trends previously reported for R

178 ,25-diol, 25HC) as a component of the sterol metabolic network linked to the IFN response via Stat1.

179 ction networks, gene regulatory networks and metabolic networks, many algorithms have been proposed f

180 Metabolic network mapping is a widely used approach for

181 These results suggest how metabolic networks may balance costs and benefits, with

182 ms, which are prohibitively slow as putative metabolic networks may exceed 1 million compounds.

183 Abnormal metabolic networks may provide markers of idiopathic rap

184 Metabolic network measurements provide a sensitive means

185 of differential gene expression data with a metabolic network model allowed us to characterize the m

186 n-based approach, which, by coupling a plant metabolic network model and transcriptomics data, can pr

187 Using the iAF1260 E. coli metabolic network model for optimization of fatty acid p

188 ously consistent with the input genome-scale metabolic network model, gene expression data, and TF kn

189 abolic network reconstructions into a single metabolic network model.

190 Stoichiometric metabolic network modeling integrated with "omics" data

191 s inherent in metabolic regulatory networks, metabolic network modeling, and interspecies studies uti

192 bacteria using metabolomics and genome-based metabolic network modeling.

193 pply MONGOOSE to the analysis of 98 existing metabolic network models and find that the biomass react

194 sets for the construction of tissue-specific metabolic network models and to constrain the range of p

195 Gene regulatory and metabolic network models have been used successfully in

196 flux mode analysis (EFMA) decomposes complex metabolic network models into tractable biochemical path

197 We use in silico metabolic network models to predict levels of competitio

198 The metabolic network of a cell represents the catabolic and

199 The curated model of the metabolic network of Anabaena sp. PCC 7120 enhances our

200 ables researchers to formulate models of the metabolic network of Arabidopsis and enhances the resear

201 Folate-mediated one-carbon metabolism is a metabolic network of interconnected pathways that is req

202 ach containing the full genome and predicted metabolic network of one organism, including metabolites

203 ach containing the full genome and predicted metabolic network of one organism, including metabolites

204 PGDB contains the full genome and predicted metabolic network of one organism.

205 daptations of microbial community structure, metabolic network of SOC decomposition, and trophic inte

206 cle, we present a visualization tool for the metabolic network of Synechocystis sp. PCC 6803, an impo

207 describes the generic and condition-specific metabolic network of Trypanosoma brucei, a parasitic pro

208 in practice, the alignment of organism-wide metabolic networks of human (1615 reactions) and mouse (

209 We apply it to metabolic networks of increasing dimensionality.

210 o have played a key role in the evolution of metabolic networks of photosynthetic organisms by connec

211 ral carbon sources and the other by creating metabolic networks of predicted genomes.

212 end to function at the interface between the metabolic networks of the host and pathogen.

213 ons are reflected in the organization of the metabolic networks of the interacting species, and intro

214 their mothers, and generate community-level metabolic networks of the microbiome.

215 er, that when homology is used with a global metabolic network one is able to predict organismal meta

216 iver models described either by genome scale metabolic networks or an object-oriented approach.

217 On directed metabolic networks, our framework yields insights into p

218 Recent studies suggest that the sterol metabolic network participates in the interferon (IFN) a

219 aper, we address the problem of aligning two metabolic networks, particularly when both of them are t

220 mediate the changes in gene expression upon metabolic network perturbations.

221 to understand the complexity of the cardiac metabolic network, pharmacological and genetic tools hav

222 The rate of metabolic network progression in this cohort was compare

223 ntegrating gene regulation data with a human metabolic network prompted the establishment of an open-

224 l approaches for analyzing dynamic states of metabolic networks provide a practical framework for des

225 enzymes and the description of genome-scale metabolic networks, providing stoichiometrically balance

226 scale models of the Saccharomyces cerevisiae metabolic network published since 2003 to evaluate progr

227 rulence-linked pathways using a genome-scale metabolic network reconstruction of Pseudomonas aerugino

228 Current methods for automated metabolic network reconstruction rely on gene and reacti

229 process of deriving a metabolic model from a metabolic network reconstruction to facilitate mechanist

230 We combine metabolic network reconstruction with metatranscriptomic

231 Genome-scale metabolic network reconstructions (GENREs) are repositor

232 Metabolic network reconstructions are often incomplete.

233 Bottom-up metabolic network reconstructions have been developed fo

234 formalized methods to quantitatively assess metabolic network reconstructions independently of any p

235 automatically reconciling a pair of existing metabolic network reconstructions into a single metaboli

236 constraints reduce the feasible space, draft metabolic network reconstructions may need more extensiv

237 We have developed reconciled genome-scale metabolic network reconstructions of B. cenocepacia J231

238 Genome-scale metabolic network reconstructions reveal metabolic diffe

239 For most metabolic network reconstructions tested, BoostGAPFILL s

240 nd integrate this modeling with genome-scale metabolic network reconstructions to identify metabolic

241 roof of concept in a set of 100 genome-scale metabolic network reconstructions, and delineate the var

242 Here, we tackle the challenge of curating metabolic network reconstructions.

243 we are challenged with understanding global metabolic network regulation and the resulting metabolic

244 r low-molecular-weight (LMW) PAHs in HMW PAH-metabolic networks remain poorly understood.

245 Redundancy in this complex metabolic network renders the rational engineering of cy

246 often been limited to targeted or simplified metabolic network representations due to computational d

247 building and analyzing models use different metabolic network representations.

248 is insufficient, whereas viewing the entire metabolic network results in information overload.

249 changed metabolites onto the phenylpropanoid metabolic network revealed partial redirection of metabo

250 Metabolic network rewiring is the rerouting of metabolis

251 example of transcriptional vitamin-directed metabolic network rewiring to promote survival under vit

252 Finally, analysis of gene and metabolic networks showed that OT triggers cell apoptosi

253 enting complex cellular processes, including metabolic networks, signal transduction and gene regulat

254 ics of 3D OCNs with 2D OCNs and with organic metabolic networks, studying the scaling behaviors of ar

255 A metabolic system refers to a metabolic network subgraph; nodes are compounds and edge

256 How primordial metabolic networks such as the reverse tricarboxylic aci

257 ts of ThiC in vivo and in vitro to probe the metabolic network surrounding AIR in Salmonella enterica

258 yotic species, the software provides several metabolic network templates, including those for chemohe

259 is less sensitive to the completeness of the metabolic network than pFBA.

260 er for annotations found in manually curated metabolic networks than those that were not.

261 (HCMV) induces numerous changes to the host metabolic network that are critical for high-titer viral

262 ndicators associated with the alterations in metabolic networks that affect complex phenotypic traits

263 nt and predictive capability of genome-scale metabolic networks that enable structural systems biolog

264 ic network one is able to predict organismal metabolic networks that have enhanced network connectivi

265 ely that there can exist different community metabolic networks that have the same metabolic inputs a

266 gnificant impact on our ability to use large metabolic networks that lack annotation of promiscuous r

267 rial scale can result in unbalanced cellular metabolic networks that reduce productivity and yield.

268 ition, pancreatic cancer cells have adaptive metabolic networks that sustain proliferation in vitro a

269 of enzymes in a microbe, the topology of the metabolic network, the environmental conditions, and the

270 As one of the key nodes in the metabolic network, the forkhead transcription factor FOX

271 eliably defines the qualitative state of the metabolic network throughout this metabolic decay proces

272 produce biomass, influence the state of the metabolic network thus directly affecting predictions.

273 es gene expression measurements into a human metabolic network to infer new cancer-mediated pathway c

274 f candidate regulatory interactions with the metabolic network to predict their systems-level effect

275 etabolic model of tomato leaf, and used this metabolic network to simulate tomato leaf metabolism.

276 transcriptional, epigenetic, signalling and metabolic networks to constitute multi-lineage competenc

277 te determines these interaction indices from metabolic network topology, and can be used for small- o

278 ds or in the size and level of detail of the metabolic networks under consideration.

279 Maternal metabolites and metabolic networks underlying associations between mater

280 enase pointing to the robustness of the core metabolic network used by these facultative pathogenic b

281 reconstruction of the cardiac mitochondrial metabolic network using constraint-based methods, under

282 es a framework for comprehensive analysis of metabolic networks using mass balances and elementary me

283 We predict organismal metabolic networks using sequence homology and a global

284 n the development of other organism-specific metabolic network visualizations.

285 The metabolic network was constructed using the P. tricornut

286 tion of the (13)C/(15)N label throughout the metabolic network was evaluated with gas chromatography-

287 The metabolic network was systematically perturbed and its f

288 or linking the microbial network to a bovine metabolic network, we observe that these ruminal metabol

289 translated metagenomic reads to a microbial metabolic network, we show that ruminal ecosystems that

290 Focusing on pathogen metabolic networks, we review in silico strategies used

291 Fluxes through the central metabolic network were deduced from the redistribution o

292 Fluxes through the central metabolic network were deduced from the redistribution o

293 Core metabolic networks were computed from taxa and genes ide

294 Correlation-based metabolic networks were generated from the genotype-depe

295 All are members of a metabolic network where substantial cross-feeding takes

296 e effect of this biochemical activity on the metabolic network, which impacts organism fitness.

297 cted the polyamine pathway from the complete metabolic network while still maintaining the predictive

298 resent a model for this surprisingly complex metabolic network with multiple IAN sources and channeli

299 These adaptations reveal a metabolic network with the regulatory capacity to mount

300 hallenging because cells have evolved robust metabolic networks with hard-wired, tightly regulated li

301 We consider metabolic networks with known stoichiometry to address t