ライフサイエンスコーパス: experimental data

1 f environmental circumstances without actual experimental data.

2 mathematical models with which to compare to experimental data.

3 nalis voltage-sensitive phosphatase, against experimental data.

4 Ge, in complete agreement with the available experimental data.

5 chine learning of sequence patterns in known experimental data.

6 ation to provide transparent traceability of experimental data.

7 d pressure drop show good agreement with the experimental data.

8 reciprocating the available thermomechanical experimental data.

9 nd to predict morphologies in agreement with experimental data.

10 s, and reproduce simultaneously both sets of experimental data.

11 omain (TM) also was modeled and supported by experimental data.

12 uared error (RMSE) between the model and the experimental data.

13 K and supported our simulations by strategic experimental data.

14 benchmarking the method against independent experimental data.

15 We tested BFDCA using simulation data and experimental data.

16 fied to be rapidly established directly from experimental data.

17 es or by fitting trial model Hamiltonians to experimental data.

18 ood agreement with available simulations and experimental data.

19 t agar, we evaluate the fit of this model to experimental data.

20 raints and explain equally well the observed experimental data.

21 yields of the samples, accurately reproduce experimental data.

22 computational model that is calibrated using experimental data.

23 that satisfies the many constraints from our experimental data.

24 drug and drug combinations in agreement with experimental data.

25 ation and semi-quantitatively reproduces the experimental data.

26 se relationships has used statistical fit to experimental data.

27 urons and connections and fitted them to the experimental data.

28 ypotheses and alternative interpretations of experimental data.

29 c moduli of skin, which correlated well with experimental data.

30 ition of catalytic activity, consistent with experimental data.

31 show that the model can describe a wealth of experimental data.

32 ion accessibility from the analysis of these experimental data.

33 ing system via simulation and validated with experimental data.

34 the halide series in good agreement with the experimental data.

35 ramework is of high-quality when assessed by experimental data.

36 opological structures of RNAs guided by some experimental data.

37 troscopy (2DES) and Redfield modeling of the experimental data.

38 er thickness were calculated on the basis of experimental data.

39 parameter space that are consistent with the experimental data.

40 d for the statistical evaluation of obtained experimental data.

41 argon gas while lower values are promoted by experimental data.

42 unseen samples, as evaluated by independent experimental data.

43 onnecting a computational model closely with experimental data.

44 rom a simple genetic oscillator model and in experimental data.

45 or power-law rheology (PLR), best suits the experimental data.

46 demonstrated to be unique for explaining our experimental data.

47 distance, both in polymer simulations and in experimental data.

48 response accounts for previously unexplained experimental data.

49 a bi-layer structure qualitatively fits the experimental data.

50 Together, these analyses explain our experimental data.

51 eights may be made accurate by incorporating experimental data a posteriori.

52 According to the present clinical and experimental data, a time window between days 4 and 7 po

53 Very recent experimental data about the immunopathology and the dete

54 We also demonstrate the techniques on experimental data acquired using the image reconstructio

55 ing computational evidence in the context of experimental data allowed us to conclude that three chem

56 hanism in more detail than is possible using experimental data alone however, and in particular we un

57 These experimental data along with computational results indic

58 oretical models based on this mechanism with experimental data, an unrealistically large structural c

59 l migration in a tail-bud-like geometry with experimental data analysis to assess the importance of o

60 Combined experimental data (analysis of guard cell wall epitopes

61 Experimental data and analytical modelling show that myo

62 calibrated by existing in vivo and in vitro experimental data and can be used over a wide range of f

63 dely applied to analyze large-scale CLIP-seq experimental data and can provide a practically useful t

64 Both experimental data and computational results suggest that

65 the results of the DFT calculations with the experimental data and confirm that the computed free ene

66 ragg curve and resolve discrepancies between experimental data and current RBE models.

67 Based on our experimental data and density functional theory calculat

68 The experimental data and DFT calculations of biaryls with d

69 oung's modulus are derived and compared with experimental data and empirical results.

70 s proposed that is consistent with available experimental data and explains the observed evolution of

71 ory and inhibitory neurons could predict the experimental data and helped interpret these results.

72 ults show reasonable agreement with reported experimental data and indicate that key molecular proces

73 redictions for xanthine derivatives with new experimental data and literature-based evidence delineat

74 computational platforms for contextualizing experimental data and making functional predictions for

75 Our experimental data and model demonstrate that an elastic

76 odeling approach to unambiguously understand experimental data and more generally to study contaminan

77 Here, by combining previously reported experimental data and our own density-functional theory

78 Structure data, aligned sequences, experimental data and prediction scores for test-cases,

79 te the IF method by using both simulated and experimental data and provide an ImageJ plugin for deter

80 Rather, our experimental data and results from biophysically realist

81 The results are in excellent agreement with experimental data and results of full ab initio calculat

82 facilitate the mechanistic interpretation of experimental data and serve as a next-generation method

83 The analysis of the experimental data and simulation results suggested that

84 can be assessed by their overall fit to the experimental data and stereochemical information.

85 Using single cell experimental data and the developed method, we compute f

86 aking into account the agreement between the experimental data and the theoretical results, it is con

87 The experimental data and theoretical analysis show that our

88 Gompertz model was used to fit the experimental data and to assess the influence of the mol

89 ation could not be directly deduced from the experimental data, and alternative pairing geometries co

90 f logic-based dynamic models, trains them to experimental data, and combines their individual simulat

91 The method was tested on both synthetic and experimental data, and consistently demonstrated perform

92 ith previously published and newly generated experimental data, and suggested new in vivo experiments

93 These predictions are supported by experimental data, and the design principles derived fro

94 provide over 140 novel predictions for which experimental data are currently lacking.

95 Despite enthusiastic agreement that experimental data are directly relevant for determining

96 The experimental data are explained by a family of random-wa

97 Additional situations and applications to experimental data are explored in SI Appendix In the pre

98 nd their comparison with currently available experimental data are helpful in identifying a specific

99 The experimental data are in good agreement with particle tr

100 sed as driving mechanisms, but the available experimental data are insufficient to distinguish betwee

101 lutants, including perchloroethylene (PERC), experimental data are lacking, resulting in default assu

102 rvational data is needed because large-scale experimental data are not forthcoming.

103 Henry's constants for systems where reliable experimental data are scarce.

104 However, as these experimental data are sensitive to many structural and d

105 The experimental data are shown to be in agreement within le

106 n remains yet to be fully understood because experimental data are still sparse in that regard.

107 The experimental data are supported by a model to show how o

108 The obtained experimental data are used to feed a 2D mathematical and

109 In the warm dense matter regime, experimental data are very scarce so that many theoretic

110 This tool is then deployed on novel experimental data as a proof of concept, illustrating th

111 It provides a site for authors to deposit experimental data as well as detailed information on met

112 This assumption guides the interpretation of experimental data, as changes in the crystal symmetry ha

113 Other than numerous experimental data assessing phage therapy efficacy, ques

114 Here, we present experimental data at 1-3 GPa, 800 degrees C, and FMQ app

115 Here, we report experimental data at low projectile velocities near the

116 Besides being in agreement with the experimental data available for selected isomers at very

117 ene in THF, a catalytic system with abundant experimental data available.

118 ermodynamic models, relying on a very sparse experimental data base.

119 n thermodynamic models rely on a very sparse experimental data base.

120 Diffusivity was extracted from experimental data based on "regular regime approach".

121 (3 reactions, 17 constants) represented the experimental data better than the previously published m

122 thod will not only improve the evaluation of experimental data, but also allow for better statistical

123 ons are able to adequately describe observed experimental data, but insufficient supply of electron d

124 A 3-state kinetic model fits the experimental data, but only if it includes a concentrati

125 ectly obtained from heterogeneous nucleation experimental data by a recently developed analysis metho

126 The experimental data can be well reproduced by numerical si

127 s able to capture and predict a large set of experimental data concerning the host and its foreign ge

128 The experimental data demonstrate that the local borepin rin

129 A mathematical model based on our experimental data demonstrates how differential phosphor

130 ion channel models with one another and with experimental data difficult.

131 hods for physics-based, knowledge-based, and experimental data-directed modeling for RNA structures a

132 This report presents experimental data directly connecting the macroscopic sh

133 Analysing experimental data for 20 fish species, we found size-tem

134 VEPART begins with time course experimental data for a sample population, and a mathema

135 Experimental data for demagnetized samples confirm most

136 ensive database that collects and summarizes experimental data for Escherichia coli K-12, the best-st

137 ere, by integrating population genetics with experimental data for growth and mineralization, physiol

138 ical results are in agreement with published experimental data for realistic assumptions of these par

139 or compared with the closed receptor; and 2) experimental data for receptor activation using the agon

140 The model predictions were compared with the experimental data for specific porous media and good agr

141 The results provide quantitative experimental data for testing theoretical models of stab

142 The model is calibrated with new experimental data for the LuxAB and Fre reactions from P

143 vide insight into binding modes in line with experimental data for these receptors.

144 We support our analysis with experimental data for two distinct enantioconvergent pro

145 The model is fit to experimental data for young and old mice infected with i

146 deed, the recent integration of quantitative experimental data, force measurements and mathematical m

147 erms of DNA double strand breaks, agree with experimental data found in the literature (pulsed field

148 Comparing experimental data from 3D and 2D amorphous solids with 2

149 We compare the results of our model to experimental data from a recent laboratory study of biot

150 the Z Chromosome, based on computational and experimental data from chicken and zebra finch, and acts

151 With statistically significant experimental data from cryogenic to high temperatures, w

152 With our model, we simulate experimental data from four seminal studies that microst

153 vidually or as an ensemble against long-term experimental data from four temperate grassland and five

154 Testing our approach with simulated and experimental data from GFP-labeled kinesin-1 motors step

155 eters were estimated by fitting the model to experimental data from guinea-pig pancreatic ducts.

156 We also present new experimental data from size exclusion chromatography tha

157 Calibrated and validated using clinical and experimental data from the literature, the model predict

158 s based on limited evidence and virtually no experimental data from the pediatric population.

159 APSIM accurately reproduced experimental data from the Soybean Free-Air CO2 Enrichme

160 nogenicity and immunogen re-design, based on experimental data generated by us and others over the pa

161 Recent experimental data has suggested that the underlying path

162 ers analyzed using as input the voltammetric experimental data (i.e. r>0.9).

163 Specifically, our experimental data in mouse hippocampal slices show that

164 up of proto-peptides, yet there is a lack of experimental data in support of this.

165 We then show its application to experimental data in x-ray and electron nanotomography.

166 d compare biological networks, inferred from experimental data, in a fast and principled way.

167 The agreement between model and experimental data indicates that the anisotropic contrac

168 We integrate a variety of experimental data into a crosstalk network, which reveal

169 strate how the approach allows us to dissect experimental data into a number of dynamic processes bet

170 Incorporating experimental data into constraint-based models can impro

171 Integration of experimental data into our model revealed significant va

172 Therefore, incorporating quantitative experimental data into tissue level simulations reveals

173 Furthermore, a variety of additional experimental data is available to support computational

174 methods to be employed when only one set of experimental data is available, though modest results we

175 Experimental data is limited in scope and generally corr

176 Experimental data is used to study microstructural effec

177 phic modelling, grounded in observational or experimental data, is therefore necessary to better unde

178 s, its simulated STM image perfectly matches experimental data, it is more thermodynamically stable t

179 After examination with the published experimental data, it is thus confirmed that the model c

180 f 0.025 A, approximately the accuracy of the experimental data itself.

181 Consistent with experimental data, MD runs in the absence of Ca(2+) and

182 cover, explain and unravel a wide variety of experimental data obtained during the electrical degrada

183 We report experimental data obtained for a micrometer scale Y3Fe2(

184 -squares fitting of the model predictions to experimental data obtained from isolated ducts and intac

185 This conclusion was supported by experimental data obtained in HeLa cells transfected wit

186 The comparison of experimental data obtained in neat acetonitrile with dat

187 Comparisons to the analogous experimental data obtained in pentane and computational

188 mpared and contrasted this intermediate with experimental data obtained in spectroscopic, crystallogr

189 This model is used to reproduce experimental data obtained on a bistable system and to i

190 The NMR experimental data obtained were confirmed by DFT quantum

191 When provided with omics and experimental data, ODG will create a comparative, multi-

192 Experimental data of ethanol and dimethyl sulfoxide are

193 mately 6.5 provides an excellent fit for the experimental data of liquid argon, for a range of thermo

194 sly published small-angle neutron scattering experimental data of the filamentous hemagglutinin adhes

195 l Bayesian uncertainty quantification We use experimental data of the radial distribution function an

196 Experimental data of vinculin during various stages of t

197 ement in an integrative manner the available experimental data on [Formula: see text], providing quan

198 her benchmark our predictions with published experimental data on aggregation hotspots and solubility

199 n to be consistent with previously published experimental data on binding rate changes with respect t

200 This model was carefully calibrated with the experimental data on helical content and affinity, and s

201 bular proteins has been extensively studied, experimental data on IDPs at the air/water (A/W) and wat

202 an atria was updated to incorporate detailed experimental data on IKur from both wild-type and mutant

203 Here, we summarize the experimental data on periodic lateral root priming.

204 rt from collecting and reassessing available experimental data on protein-protein interactions, and i

205 l while being simultaneously compatible with experimental data on structure, connectivity, and neurop

206 mparing the results of calculations with the experimental data on the dynamics of the potential chang

207 isotope effects, and the first quantitative experimental data on the effects of aryl electron demand

208 We obtained experimental data on the expression of 22 genes across f

209 Initially, experimental data on the uptake of the three chemicals a

210 ion of the confined interior compatible with experimental data on unperturbed adenoviruses and polyom

211 Using published experimental data on virus inactivation rates in wastewa

212 In the context of available experimental data, our findings support the deleterious

213 Comparing model predictions with these experimental data, our model successfully predicts the t

214 -dependence, we find an excellent fit of the experimental data over the full range of irradiation ang

215 ustom software for integrating modeling with experimental data processing workflows, facilitated by a

216 The marked improvement of experimental data promises to provide access to increasi

217 Our simulations and experimental data provide evidence that cohesin-dependen

218 The results reproduce experimental data, providing insights into events relate

219 cal approach is verifiedusing thepreexisting experimental data published elsewhere.

220 ivatives, resulting in strong agreement with experimental data (R(2) = 0.78).

221 A second-order polynomial fitted the experimental data (R(2): 0.9736; p-value <0.0001).

222 ss, the inference of signaling networks from experimental data remains very challenging.

223 show strong overall agreement with published experimental data, reproducing the shapes of experimenta

224 Our simulated and experimental data reveal for the first time that positio

225 The experimental data reveal the unfolding pathway in unprec

226 Our experimental data revealed complex burst-like time evolu

227 s demonstrated by its application to a large experimental data set obtained in the untargeted LC x LC

228 Two experimental data sets available from different studies

229 Model performance is assessed using seven experimental data sets extracted from three different st

230 e performance of our method on synthetic and experimental data sets from two colorectal cancer patien

231 due to limitations of training on available experimental data sets, alternative approaches that util

232 ng simulated data, and then apply it to four experimental data sets.

233 t, very similar to light output seen in some experimental data sets.

234 Clinical and experimental data show that breast tumors treated with a

235 Recent experimental data show that CaM selectively promotes K-R

236 However, our experimental data show that the protein does not transfe

237 luation of predictions against corresponding experimental data showed good predictions of uptake for

238 s and thermodynamic results derived from the experimental data showed that the interaction between co

239 kingly, the HS models were validated against experimental data showing a remarkable agreement with ca

240 Here, we present further experimental data showing that inhibition of interferon-

241 Comparison with experimental data shows that the model allows quantitati

242 The experimental data sources from a nested case-control stu

243 All of our experimental data stay within these physical boundaries

244 Unfortunately, routinely and easily measured experimental data such as growth rates, extracellular fl

245 data and analysis tools with other types of experimental data such as RNA-seq or ChIP-seq.

246 PLUMED-ISDB implements different types of experimental data, such as several NMR observables, FRET

247 Our clinical and experimental data suggest a correlation between age at d

248 Results of using experimental data suggest that BFDCA can cluster disease

249 Overall, our experimental data suggest that CLIP170 serves as an intr

250 Genetic and experimental data suggest that efferocytosis is impaired

251 Our experimental data suggest that reversible protonation of

252 Our experimental data suggest that schizonts are at the bord

253 Recent experimental data suggest that the majority of CD4(+) T

254 ctronic structure calculations correlated to experimental data suggest that this state is best repres

255 Our experimental data suggests that the microgels form a cor

256 A model developed based on the experimental data suggests that the thermal conductivity

257 e in better agreement with the benchmark and experimental data than are the NSF results in all studie

258 rther present a compilation of nanoplasmonic experimental data that are excellently described by the

259 Experimental data that meet these requirements can be ob

260 a mathematical model that was constrained by experimental data (the expanded disability status scale

261 seq in mapping TF provides a large amount of experimental data to analyze co-TFs.

262 approaches can be successfully coupled with experimental data to characterize responsive DNA-based n

263 roduces the capability to use (13)C labeling experimental data to constrain comprehensive genome-scal

264 In this study we use both synthetic and experimental data to demonstrate that the determination

265 Furthermore, we used MCORE to compare our experimental data to models for heterochromatin reorgani

266 The group-contribution model uses limited experimental data to obtain group-interaction parameters

267 ction has been gained from the comparison of experimental data to receptor models.

268 ose tissue, and umbilical cord have the most experimental data to support their potential efficacy fo

269 ations shows an excellent agreement with the experimental data to within 8%.

270 Rather, our experimental data, together with computational modeling,

271 es stems from the treatment of heterogeneous experimental data used to predict the architecture of na

272 ve uptake coefficients were derived from the experimental data using GAMMA 4.0.

273 ites where the correlation between FoldX and experimental data vanishes, the profile-based calculatio

274 tures, making access and manipulation of the experimental data very natural within Python programs (i

275 es) model employed in this study matched our experimental data very well and provides mechanistic ins

276 Validation of a theoretical model using the experimental data was done in order to predict the Lewis

277 erical methods to assess the accuracy of the experimental data, we measured flow profiles and drag fo

278 On the basis of these experimental data, we propose a tentative mechanism inte

279 Based on experimental data, we propose that adenosine triphosphat

280 iven the epidemiological evidence and recent experimental data, we propose that this concept should a

281 he highest agreement between simulations and experimental data were associated with energy metabolism

282 The experimental data were in consistence with the DFT calcu

283 Experimental data were used to define CO2 uptake rates a

284 ze basepairing probabilities guided by SHAPE experimental data when such data are available.

285 Instead, our experimental data, when coupled with a mathematical mode

286 lize published genomics data integrated with experimental data which can be queried using a flexible

287 In this Topical Review we discuss the experimental data which suggest UPS dysfunction is a com

288 We discuss here recent experimental data which, at a minimum, fully substantiat

289 th existing low-temperature ambient pressure experimental data, which are shown to be inconsistent wi

290 eloped using a large data set of homogeneous experimental data, which is also disclosed as Supporting

291 ed domain overlap score of 89.3% compared to experimental data, which is significantly higher than ot

292 ar machine models that successfully describe experimental data, which suggests that, in evolved machi

293 Experimental data will guide further optimization of the

294 However, we were able to fit the experimental data with a more general network class, of

295 The analysis of the experimental data with a newly developed theoretical mod

296 ionally heterogeneous systems by integrating experimental data with a priori information.

297 ystems can be obtained by properly combining experimental data with a priori physico-chemical knowled

298 ctant mixtures that is based on a fit of the experimental data with cubic splines using a stringent t

299 peutically relevant compounds in cases where experimental data yielded inconclusive or ambiguous resu

300 An analysis of the experimental data yields high fill factors of approximat