ライフサイエンスコーパス: modeling

1 MP, a general framework for membrane protein modeling.

2 range of elements by mechanistic geochemical modeling.

3 ry records and supported by marine ecosystem modeling.

4 transplant on the basis of multivariable Cox modeling.

5 ps were tested by using linear mixed-effects modeling.

6 r (1-5 kt yr(-1)), as indicated by numerical modeling.

7 that can accommodate time-dependent exposure modeling.

8 ing MLL-FP driven leukemias ideal for animal modeling.

9 ipal outcome was explored with multivariable modeling.

10 biology to regenerative medicine and disease modeling.

11 mentally and by means of kinetic Monte Carlo modeling.

12 icago using agent-based transmission dynamic modeling.

13 multiplex genome engineering and predictive modeling.

14 yzed by longitudinal nonlinear mixed-effects modeling.

15 ve way to improve the quality of flexibility modeling.

16 subject for biological research and disease modeling.

17 ldhood, identified using latent class growth modeling.

18 nar depth were determined with mixed-effects modeling.

19 otting, mass spectrometry, and computational modeling.

20 d from serological data using finite mixture modeling.

21 king, named OPUS-DOSP, for protein structure modeling.

22 ration (B) to be independent for use in fate modeling.

23 without DM were evaluated using multivariate modeling.

24 y generalized linear mixed method regression modeling.

25 ntegrates cellular behaviors via agent-based modeling (ABM) and hemodynamic effects via computational

26 n opportunities and accessibility of kinetic modeling across the field.

27 ses and multivariate Cox proportional hazard modeling, adjusted for treatment, patient age, year of d

28 The novel dose-response modeling algorithm has been tested against millions of d

29 Multivariable modeling also showed that dermatology consultations were

30 Mutational and modeling analyses indicated that an evolutionarily conse

31 Based on mutational, kinetic and modeling analyses, a catalytic mechanism involving leavi

32 Using modeling and anatomy, we show that realistic input patte

33 mental results, a combination of theoretical modeling and atomistic simulations indicates that the fo

34 Both the theoretical modeling and atomistic simulations predict that the adhe

35 natomy to electrophysiology to computational modeling and behavior.

36 Computational modeling and cellular mutational analysis revealed the h

37 principles of cellular automata/agent-based modeling and combine it with very detailed empirical dat

38 Here, de novo Rosetta modeling and competitive binding experiments show that t

39 portunities and challenges in RNA structural modeling and design, as recently discussed during the se

40 ced amino acid sequence, phylogeny, homology modeling and docking simulation.

41 xcluding adaptation, irrespective of climate modeling and emissions uncertainty, can be as low as 28%

42 ew explores recent advances in computational modeling and empirical research aimed at addressing thes

43 Moreover, this study establishes a modeling and experimental method to elucidate the struct

44 hrough an iterative process of computational modeling and experimental tests, we found that these mem

45 ng in its unique properties using analytical modeling and experiments.

46 ation in coupled nutrient cycles, as well as modeling and forecasting nutrient controls over carbon-c

47 e (NIAID) workshop 'Complex Systems Science, Modeling and Immunity' and subsequent discussions regard

48 Homology modeling and in silico analysis of the GmSACPD-C enzyme

49 Structural modeling and molecular simulations reveal unique hydroph

50 ecedented opportunities for in vitro disease modeling and personalized cell replacement therapy.

51 nt-specific differentiated cells for disease modeling and preclinical drug testing.

52 expands the capability of protein structure modeling and provides crucial insights into the molecula

53 46% when including tacrolimus variability in modeling and reduced by 40% for graft loss.

54 lication of hPSC-derived lineages in disease modeling and regenerative medicine.

55 have potential applications for both disease modeling and regenerative medicine.

56 rvival were analyzed using multivariable Cox modeling and restricted cubic spline function.

57 the latest developments in the mathematical modeling and simulation techniques that have been report

58 We explored, through mathematical modeling and simulations, the size of potential effects

59 Molecular modeling and site-directed mutagenesis implicate several

60 Molecular modeling and studies on VDRE-transcriptional activity ex

61 Furthermore, by combining computational modeling and the BiLC reporter assay, we identified seve

62 tions with the precision needed for economic modeling and the simplicity needed for lay respondents.

63 for translational research as they may allow modeling and therapy of human diseases in vivo.

64 tionality of these links through statistical modeling and verifying our findings with computational m

65 tion maximization with point-spread function modeling) and were examined qualitatively.

66 A combination of spectroscopy, computational modeling, and crystallography has identified the structu

67 ated opportunities for heart repair, disease modeling, and drug development.

68 tal biology, regenerative therapies, disease modeling, and drug discovery.

69 order to support precision medicine, disease modeling, and mechanistic exploration.

70 igh-throughput data acquisition, data-driven modeling, and mechanistic modeling to define new mechani

71 discuss the benefits and limitations of each modeling approach and their value for clinical applicati

72 This modeling approach could serve as an early warning system

73 An alternative multivariate modeling approach that categorizes hospital readmissions

74 Here, we present a coupled experimental/modeling approach to establish an in vitro pharmacokinet

75 olomic, biochemical, fluxomic, and metabolic modeling approach was developed using 19 genetically dis

76 s proposed based on a multi-response kinetic modeling approach.

77 t Cd end-members was confirmed by a Bayesian modeling approach.

78 A number of modeling approaches have been developed to predict the i

79 h throughput screen and subsequent in silico modeling approaches.

80 We used mathematical modeling as a theoretical framework to bridge between ex

81 Multivariable logistic regression modeling assessed the independent effects of restrictive

82 ring studies of sTie2 dimers in solution and modeling based on crystal structures, we suggest that An

83 This Review focuses on classical metal ion modeling based on unpolarized models (including the nonb

84 A trajectory modeling, based on hematocrit evolution pattern, allowed

85 pendent phenotype including behavior changes modeling bipolar disorder, epilepsy and sudden death.

86 This new concept of metabolic disease modeling by somatic genome editing could be applied to m

87 Modeling C1q status showed that C1q-positive patients ha

88 As predicted by molecular modeling calculations, rotation around the bond connecti

89 Computational modeling can aid in identifying neural generators of fie

90 Pattern-process modeling can provide qualitative and quantitative means

91 ates the ability of the developed method for modeling cell decision making errors under normal and ab

92 e achieved through collaboration between the modeling community and public health policy community.

93 atistical nondeterministic model, capable of modeling complex patterns of trophic control for the hea

94 Behavioral results and computational modeling confirmed that learning was best explained as a

95 this study provides a unified framework for modeling continuum and rarefied gas flows.

96 ess of newly polymerized MTs, and structural modeling data suggest a conformational change in the alp

97 Human cell modeling demonstrated reduced expression from the mutant

98 Leaf-level modeling demonstrated that current parameterization of T

99 cy: selection by a medicinal chemist, manual modeling, docking followed by manual filtering, and free

100 a key challenge for applications in disease modeling, drug screening, and heart repair.

101 tion from all available markers, rather than modeling effects of individual loci.

102 We evaluate important modeling efforts for establishing how crosstalk between

103 Ecological niche modeling (ENM) has been used to address such questions,

104 ation of target quantity, when using Poisson modeling, especially at higher concentrations.

105 Longitudinal panel modeling evaluated association between annual SMR change

106 Computational modeling evaluates drug vascular extravasation and diffu

107 root-mean-squared error) of load estimates a modeling exercise showed that passive samplers were a vi

108 Our results show that statistical modeling extends the scope and potential of transcriptom

109 ng on Template Based Modeling (TBM) and Free Modeling (FM)/TBM targets.

110 Hypothetical bypass modeling for all transferred patients suggested that int

111 bed, and analyzed by using linear regression modeling for group differences.

112 wledge-based, and experimental data-directed modeling for RNA structures and explore the new theories

113 s from FOSA partitioning and bioaccumulation modeling forced by changes in atmospheric inputs reasona

114 Next, we develop a modeling framework that leverages transfer learning to i

115 hysiology into a quantitative, comprehensive modeling framework, we show how water flow in the colon,

116 ential components of an emerging 'respectful modeling' framework which has two key aims: (i) respecti

117 l for assessing past climate sensitivity and modeling future climate scenarios.

118 s) have been proposed, but their accuracy in modeling GIDs has been questioned because they usually r

119 between these mechanisms by computationally modeling goal-directed and habitual behavior as model-ba

120 We carried out a survey among modeling groups to show an evolution from models able on

121 Comprehensive finite element method (FEM) modeling has been undertaken to enhance understanding of

122 Experimental modeling has defined a cooperative role of activated eos

123 With the goal of modeling human disease of the large intestine, we sought

124 te the potential use of the visual streak in modeling human macular diseases.

125 This modeling ignores the different contributions of differen

126 of population genetics and ecological niche modeling in understanding gene flow history.

127 spatial biases), and Bayesian computational modeling (in the analysis of individual subjects' use of

128 perimental data, together with computational modeling, indicate that FGF10 modulates the range of Wnt

129 Computational modeling indicated that Group II motoneurons are the maj

130 Modeling indicated that, while the increase in pH halts

131 Molecular modeling indicates that CD16A TM residues F(202), D(205)

132 Thermodynamic modeling indicates that the exceptionally high Young's m

133 Strictly data-driven BN modeling indicates that the strength of intrachromosomal

134 evaluation of new methods, force fields, and modeling innovations on well-characterized benchmark sys

135 Modeling intra-individual fluctuations in estradiol and

136 This quantitative modeling investigation of representative synaptic transm

137 In computational biology, modeling is a fundamental tool for formulating, analyzin

138 the difference from the standard to the new modeling is positively correlated to the extent of fill

139 d with bioassay of guard cell function) plus modeling lead us to propose that polar stiffening reflec

140 in the expression of cell type and metabolic modeling markers, but less so for a subset of genes asso

141 Dirichlet multinomial mixture modeling, Markov chain analysis, and mixed-effect models

142 Finite element modeling, mechanical testing, and immunohistochemical an

143 d the effect of different marker systems and modeling methods for implementing GS in an introgressed

144 th other state-of-the-art TF-DNA interaction modeling methods.

145 tivity were explained by extensive molecular modeling (MM) and molecular dynamics (MD) computations.

146 e-associated SNVs and provide a platform for modeling morphological changes in mental disorders.

147 Jointly modeling multiple traits' genetic profiles has provided

148 ve proved a major step forward to accurately modeling multisolute adsorption equilibrium.

149 egligible direct climate change impacts when modeling NEELAND using projected air temperature and inc

150 That is, we are modeling neural activity as driven by multiple simultane

151 These molecular discoveries and metabolic modeling now serve as a foundation for future examinatio

152 Finally, computational modeling of 25 missense mutations of CYP11B1 revealed th

153 Joint modeling of a number of phenotypes using multivariate me

154 arative evolutionary analysis and structural modeling of ABHD5 and ABHD4, a functionally distinct par

155 agnetic stimulation (TMS) with computational modeling of behavioral responses.

156 oint for further steps of data analytics and modeling of biological dynamics.

157 activation energies affords accurate kinetic modeling of both isothermal and nonisothermal decomposit

158 Disease-specific, time-updated modeling of clinical data for several uveitides suggests

159 Three-dimensional modeling of Complex II suggested that several SIRT5-targ

160 , iFoldNMR, for rapid and accurate structure modeling of complex RNAs.

161 he shape of the typical flight path, (2) the modeling of covariance and anisotropy, and (3) the type

162 lities between categories of BP using Markov modeling of cross-sectional data from the National Healt

163 des a rich resource for future computational modeling of E. coli gene regulation, transcription, and

164 hese parameters for use in future predictive modeling of eDNA transport.

165 DelPhiForce web server enables modeling of electrostatic forces on individual atoms, re

166 We combine mathematical modeling of genome evolution with comparative analysis o

167 s for large bulky residues, incorporated the modeling of glycans on the surface of gp120, and utilize

168 he interpretation of experiments and for the modeling of glyoxal chemistry both at the interface of w

169 Flow cytometric assessment and mathematical modeling of intraerythrocytic parasite development revea

170 Accurate atomic modeling of macromolecular structures into cryo-electron

171 a useful tool for all researchers working on modeling of macromolecules, structure prediction, proper

172 rature (SM/ST) can significantly improve the modeling of mesoscale deep convection is tested over the

173 the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME

174 ered that will further enhance the classical modeling of metal ion-containing systems.

175 s of detailed experiments and finite element modeling of metal micro-droplet motion associated with m

176 Here, we show that modeling of neural sound representations in terms of fre

177 censoring 365 days after prior screen, with modeling of occult cancers detected at RRSO.

178 Modeling of phenotypes for multilocus genotype classes i

179 Using kinetic modeling of protein dynamics, we classified the stimulus

180 Molecular modeling of selected target compounds bound to Top1, Tdp

181 asurements from mice of either sex to inform modeling of sparse and filopodia-bearing mossy fibers, f

182 at, when news coverage is uniform, efficient modeling of temporal topic trends using time-series regr

183 Such process requires modeling of the brain using graph theory and the subsequ

184 sed differences between conditions by linear modeling of the data.

185 Comparative modeling of the DNA-binding domain of human HSF1 facilit

186 echanism of this phenomenon by computational modeling of the energy barrier that the system must over

187 Modeling of the fractionation during Fe(III) sorption to

188 The DFT simulation and kinetic modeling of the nitroso oxide transformations as well as

189 Modeling of transcriptional regulatory networks (TRNs) h

190 In general, modeling oil-recovery is a challenging problem involving

191 make code they produce for data analysis and modeling open source, and are actively encouraging their

192 s well as to establish phenotypes in disease modeling or toxicity studies.

193 nce changes on SUVRs and noninvasive kinetic modeling outputs.

194 such as standard molecular dynamics and cell-modeling packages.

195 , epidemiology, genomics, cost-effectiveness modeling, pathology, bioethics, and patient advocacy to

196 Computational modeling performed with the all-atom MD simulations for

197 Structural homology modeling predicts that this protease adopts a fold and a

198 Our mathematical modeling proposes that the observed spectral tuning of s

199 The successful modeling provides additional support for biophysical pri

200 vival in all LVAD patients (n=111) using Cox modeling, receiver-operator characteristic (ROC) curves,

201 (i.e., the inclusion/exclusion of adaptation modeling) relative to using multiple climate models and

202 The modeling results also demonstrate the broader significan

203 The combined interpretation of modeling results and measured data reveals that high cU(

204 facilitating the reproduction and update of modeling results by other scientists, and (ii) respectin

205 The modeling results predict the kinetics of the process of

206 Moreover, the modeling results reveal that light-based interventions m

207 The modeling results show that groundwater recharge containi

208 However, based on modeling results, nutrients seem efficiently retained in

209 Together with linear modeling results, these findings suggest that most trans

210 antifying the confidence associated with the modeling results.

211 Mixed-effects modeling revealed a significant week-by-group interactio

212 Multivariate modeling revealed immunoglobulin heavy chain variable ge

213 3D protein modeling revealed that the 3 variants affect highly cons

214 ol of Rho-kinase combined with computational modeling reveals that active Rho-kinase diffuses to grow

215 Mathematical modeling reveals that long-term immunological memory is

216 Modeling reveals that the pool of maternal Vg1 enables r

217 A standard epidemiologic approach for modeling risk factors of a categorical outcome typically

218 d the central role that stochastic financial modeling should play in support of strategically aligned

219 Moreover, experiments and modeling show that the select-field amplitude is bead-si

220 Finally, we report the use of molecular modeling simulations to elucidate the phase-change mecha

221 ased the predictive power of the integrative modeling strategy enabling more accurate protein assembl

222 wledge about axonal conductance derives from modeling studies or indirect measurements.

223 Computational modeling studies revealed that HN is preferred at the FD

224 Moreover, modeling studies suggested that B. subtilis sigma1.1 req

225 In agreement with previous experimental and modeling studies, key factors influencing the distributi

226 In addition, molecular modeling study demonstrated that A binding sites of BSA

227 ptor crystal structures, we also performed a modeling study that sheds light on the crucial interacti

228 Molecular modeling suggested a number of amino acids in RRM1 likel

229 Ecological niche modeling suggested that a gradual range expansion of P.

230 Analytical modeling suggests that crosstalk should overwhelmingly a

231 Finite-element modeling suggests that the absorption of laser pulses by

232 existing methods in the Rosetta biomolecular modeling suite for membrane proteins, we recently implem

233 The modeling takes into account the radiation and scattering

234 o our second place ranking on Template Based Modeling (TBM) and Free Modeling (FM)/TBM targets.

235 ividual-level risk factors using appropriate modeling techniques.

236 l introduction to core aspects of predictive modeling technology, and (3) foster a broad and informed

237 We show with experiment and modeling that due to lower signal to noise, contrast-inv

238 an essential input for the chemical kinetic modeling that is necessary to fully extract physics from

239 Next, we discovered through modeling that such projection patterns can enhance the e

240 by both experimental analysis and numerical modeling that these newly synthesized doped CQWs are exc

241 In modeling the Amazonian vegetation system, we include sym

242 erging as a useful theoretical technique for modeling the dynamics of correlated systems.

243 Conventional approaches to modeling the formation of such legislative coalitions ty

244 iPSC) technology offers a novel platform for modeling the genetic contribution to mental disorders an

245 ycan occupancy that was further supported by modeling the high-affinity interaction between the optim

246 However, modeling the integrated processes of HbS nucleation, pol

247 del (SPM) represents a general framework for modeling the joint evolution of repeatedly measured vari

248 By modeling the molecular weight distributions obtained und

249 Modeling the sequential use of these two orthogonal mark

250 d framework provides a convenient method for modeling the structural relationships of functional pock

251 Modeling the structure and dynamics of segregation is a

252 es, which are in turn used as restraints for modeling the structures of those analytes in solution.

253 ol Study (SOAS) emphasizes the importance of modeling the whole system to understand the controlling

254 By COMSOL modeling, the dependence of this interaction on glass sh

255 The current findings provide a route for modeling this reaction inside the SpnF active site and i

256 ition, data-driven modeling, and mechanistic modeling to define new mechanisms of immunological disea

257 X-ray spectroscopic imaging and phase-field modeling to elucidate the delithiation dynamics of singl

258 US communities), we used structural equation modeling to estimate the association between serum 1,5-A

259 We used causal modeling to estimate the impact of local air pollution o

260 re analyzed by using nonlinear mixed-effects modeling to estimate the maximum cough response evoked b

261 on, phenotypic plasticity and climatic niche modeling to evaluate plant responses and elucidate vulne

262 We used stepwise modeling to generate a model for subphenotype identifica

263 d molecular networking and three-dimensional modeling to generate chemical cartographical heart model

264 een localized experiments and regional-scale modeling to highlight that increased drought frequency a

265 lar dynamics, electrophysiology, and kinetic modeling to identify residues that contribute to gating

266 This study showcased the contribution of modeling to inform local health-care planning during an

267 We then used voxelwise modeling to predict BOLD responses based on three differ

268 work, we performed mutagenesis and molecular modeling to strategically place tags and fluorescent pro

269 A range of membrane protein modeling tools has been developed in the past 5-10 years

270 and fostered the development of quantitative modeling tools.

271 VT was determined from 2-tissue-compartment modeling using a metabolite-corrected plasma input funct

272 Our modeling, using the transient kinetic data, predicts mec

273 Importantly, in silico modeling validated that this Ser-to-Arg mutation could a

274 potential source of decodable information by modeling voxel responses based on the Hubel and Wiesel (

275 The SITAR modeling was performed separately by sex and self-report

276 Poisson modeling was used to estimate the mortality rate ratio (

277 Logistic regression modeling was used to examine associations between each c

278 ss-realm integration in spatial optimization modeling we highlight lands and waters that together ach

279 Through waveform modeling, we detected a large ultralow-velocity zone and

280 combining our measurements with biophysical modeling, we determined that the ribosomal footprint ext

281 Using in silico modeling, we discovered that anisotropic proliferation m

282 Using dispersion modeling, we estimated spatial variability in PM10 conce

283 le in short-term prediction through internal modeling, we hypothesize that right cerebellar Crus I/II

284 nd verifying our findings with computational modeling, we infer a causal relationship, namely that ch

285 ted prospectively across life and multilevel modeling, we investigated how the relationships between

286 ask and nonlinear population receptive field modeling, we map and characterize the topographic organi

287 Using structural equation modeling, we modeled illness and medication beliefs as m

288 Using template-based structural homology modeling, we now show that the ectodomain of HAP2 orthol

289 lectron microscopy imaging and computational modeling, we resolve the precise atomic structure of met

290 Through modeling, we show that the observed beam features can be

291 ular computer simulations, and thermodynamic modeling were performed to probe the mechanisms by which

292 Mathematical modeling, which included the decay kinetics of the fluor

293 ating RGGT is limited, we combined molecular modeling with biological assays to ascertain how modific

294 Combining modeling with experiments, we related stochastic phasing

295 To fill this gap, we combined computational modeling with functional neuroimaging.

296 tudy demonstrates that combining statistical modeling with public RNA-seq data can be powerful for im

297 t circumference over time using linear mixed modeling with random effects.

298 These loci prove essential to accurately modeling yeast growth in response to different environme

299 Small angle X-ray scattering and ensemble modeling yielded models of the PHn-PHc fragment that ind

300 Substitution modeling yielded significantly lower risks of CVD mortal