ライフサイエンスコーパス: probability distribution

1 r in the shape of a displacement orientation probability distribution.

2 f the harmonic mean of n observations from a probability distribution.

3 i), and broadened according to their quantum probability distribution.

4 etation of this simple and clean exponential probability distribution.

5 utions according to this dynamically-derived probability distribution.

6 resent statistical samples from the inferred probability distribution.

7 corresponding to a complex, high-dimensional probability distribution.

8 we describe each experimental condition by a probability distribution.

9 from ad hoc parameters and requires no prior probability distribution.

10 oises could be strengthened with more robust probability distributions.

11 rial carnivore species to test the fit of 12 probability distributions.

12 their conformational properties in terms of probability distributions.

13 ty associated with inferences in the form of probability distributions.

14 s applied to response problems as well as to probability distributions.

15 a mixture of several discrete or continuous probability distributions.

16 tribution consisting of log normal and gamma probability distributions.

17 Data were fit with the sum of two gamma probability distributions.

18 nformation probabilistically, in the form of probability distributions.

19 ing based on neighbor-dependent Ramachandran probability distributions.

20 ll-cycle duration follows a general class of probability distributions.

21 ing a common reference for the definition of probability distributions.

22 configurations inconsistent with the target probability distributions.

23 e graph, and vary assumptions on the fitness probability distributions.

24 options) and choice of measure for comparing probability distributions (7 options).

25 on parameters from data, we derive posterior probability distributions, allowing for uncertainty quan

26 Using probability distribution analysis to describe the propag

27 ed estimate of the variance of the step-size probability distribution and a valid statistic for deter

28 ella-sampling techniques to characterize the probability distribution and conformation preference of

29 f the necessary information, and compute the probability distribution and higher-order moments by max

30 ay be solved exactly in terms of finding the probability distribution and its moments.

31 cing a single set of equations governing the probability distribution and moments of a broad class of

32 lations that define the spatial and temporal probability distribution and orientation of a single fil

33 nature that represents a joint multivariate probability distribution and reflects conditional indepe

34 or such processes are in the tail end of the probability distribution and show that the probability f

35 ter sizes of each species follow a power law probability distribution and that such clusters have wel

36 It was confirmed by computing the committor probability distribution and the distribution of constra

37 s, we develop analytical expressions for key probability distributions and associated quantities, suc

38 This implies that neurons both represent probability distributions and combine those distribution

39 tants at different locations come from given probability distributions and do not change in time.

40 ical evidence that the brain both represents probability distributions and performs probabilistic inf

41 rns which can be described by characteristic probability distributions and well-defined spatial relat

42 a random sample of size n derived from some probability distribution, and a formula for the latter i

43 The zero-point energy, probability distribution, and chemical shift were determ

44 fects are assigned according to a continuous probability distribution, and multiple distributions hav

45 es of stable states, 2) explore the temporal probability distributions, and 3) discover small peaks i

46 This suggests a probability distribution approximating an inverse power-

47 s facilitated by the fact that most relevant probability distributions are approximately Gaussian if

48 Posterior probability distributions are constructed for all model

49 Probability distributions are derived from the ray-trace

50 tide signal of any type emits according to a probability distribution around a series of 'hot spots'

51 pension, yet still displaying an exponential probability distribution as in the second system.

52 actions differ with respect to their outcome probability distributions - as an index of flexible inst

53 estimates to generate action values, outcome probability distributions associated with alternative ac

54 ents from experts, in the form of subjective probability distributions, can be a valuable addition to

55 mechanical arrest and relaxation copy number probability distributions collapse onto a shared univers

56 feedback loops results in diminution of the probability distribution complexity.

57 ses can be modeled even better by continuous probability distributions (CPD) of rates, using only 1-2

58 e Carlo simulations, which merely sample the probability distribution, demonstrates this closure sche

59 expressing uncertainty in parameters through probability distributions derived by fitting the model t

60 s of clinical trial data, and by using prior probability distributions derived from literature review

61 relations and present a method called joint probability distribution diagram to improve the majoriza

62 Best fitting probability distributions differed among the carnivores

63 istance metric and a link-based neighborhood probability distribution displays a phase transition bet

64 We demonstrate that the traditional discrete probability distributions do not model the length distri

65 e that incorporating the dynamically-derived probability distribution does enhance the conditional pr

66 Saccharomyces cerevisiae to seven different probability distributions: DPLN, right Pareto-lognormal

67 ing uncertainty about stimuli in the form of probability distributions (e.g., the probability density

68 that sensory uncertainty is represented by a probability distribution encoded in neural population ac

69 By modeling cellular frequencies as probability distributions, EXPANDS predicts mutations th

70 ed on quantifying differences among distance probability distributions extracted from the networks.

71 fts are observed even though the conditional probability distributions extracted using the protocol o

72 measurement times, finding that displacement probability distributions fall onto the same master curv

73 Onto, is an ontology-based knowledge base of probability distributions, featuring more than 80 uni- a

74 an associated likelihood function as a prior probability distribution for a Markov-chain Monte Carlo

75 etics theory to inform us of the appropriate probability distribution for among-site variation in the

76 sk estimates were further stratified using a probability distribution for anti-JCV antibody index val

77 om weight matrices (WMs), we derive a unique probability distribution for assignments of sites into c

78 We consider the probability distribution for fluctuations in dynamical a

79 We study the limiting probability distribution for the bivariate process, cond

80 This uncertainty is modelled as a probability distribution for the chance of conceiving in

81 We find a Gaussian probability distribution for the first few excited mode

82 radial distribution functions and occupancy probability distributions for adult mice.

83 RNA secondary structure ensembles define probability distributions for alternative equilibrium se

84 eriments using visual stimuli with symmetric probability distributions for contrast cannot reveal whe

85 iques, we have collected transfer efficiency probability distributions for dye-labeled, denatured pro

86 In order to define probability distributions for each parameter, informatio

87 m California oil fields are used to generate probability distributions for eight oil field parameters

88 Markov Chain Monte Carlo method to estimate probability distributions for estradiol- and time of day

89 of natural scene statistics reveals that the probability distributions for light increments and decre

90 Both models and observations yield broad probability distributions for long-term increases in glo

91 d us to measure the frequency of looping and probability distributions for loop size and unbinding fo

92 Specifically, we calculate probability distributions for microscopic density fluctu

93 generate correlated samples used to estimate probability distributions for parameters of interest.

94 SubSynMAP generates probability distributions for that reveal the functional

95 tions yielded the following key results: 1), probability distributions for the values of individual m

96 More robust two-dimensional distance-angle probability distributions for two pharmacophore models d

97 Some examples include: identical probability distributions for wild types and mutants; ca

98 ive, yet effective, formula for estimating a probability distribution from a sample of data.

99 rotein chain, and the functional form of the probability distribution from which they originate.

100 ehavior of the mean flow with a sub-Gaussian probability distribution function (pdf) for its fluctuat

101 The probability distribution function (PDF) of CTT for dust-

102 andelbrot and Fama proposed a symmetric Levy probability distribution function (PDF) to describe the

103 e nearly Gaussian behavior in the associated probability distribution function and without a signific

104 -particle reconstruction is interpreted as a probability distribution function based on the average o

105 This approach results in a subvoxel scaled probability distribution function whose shape correlates

106 s dynamic substrate envelope, described by a probability distribution function, is a powerful tool fo

107 an be accounted by adapting conveniently its probability distribution function, which in turn may cha

108 g below detects data as a truncated Gaussian probability distribution function.

109 tion between the dispersion and shape of the probability distribution functions best describing the s

110 al fiber populations identified within these probability distribution functions can then be associate

111 tural scenes in which we could determine the probability distribution functions of co-occurring targe

112 Bayesian age modelling was used to generate probability distribution functions to determine the late

113 field plot data, remote sensing disturbance probability distribution functions, and individual-based

114 These processes are implemented by means of probability distribution functions.

115 me isotropic diffusion and directly measured probability distributions functions for displacements.

116 Probability distributions having power-law tails are obs

117 aling on the emergence of different types of probability distribution in empirical observation.

118 present development is the construction of a probability distribution in face space that produces an

119 th the sample size, we cannot visualize this probability distribution in its entirety, unless the sam

120 ut the need to simulate the evolution of the probability distribution in time.

121 Two-dimensional distance-dihedral angle probability distributions in a third pharmacophore model

122 mechanics (MM) for the prediction of rotamer probability distributions in the crystal structures of p

123 avel patterns collapse into a single spatial probability distribution, indicating that, despite the d

124 ession periods in human EEG followed a gamma probability distribution indicative of a deterministic p

125 ntropy models describing the measured neural probability distributions, interpreting this phase trans

126 In the first kind, a probability distribution is calculated for the number of

127 A probability distribution is constructed for the structur

128 In years in which the forecast probability distribution is different from that of clima

129 To test whether such a posterior probability distribution is represented in the OFC, we t

130 iven action considered in a current state, a probability distribution is specified over possible outc

131 ost recent algal ancestors confirms that the probability distribution is widely conserved and indepen

132 We show that the shape of these probability distributions is an inevitable and general c

133 sampled subnets belong to the same family of probability distributions is it possible to extrapolate

134 With discrete probability distributions it is not possible to specify

135 ts relative area according to an exponential probability distribution known as the Gibbs measure.

136 ensemble that is consistent with one or more probability distributions known a priori, e.g., experime

137 sian sampling technique developed to explore probability distributions localized in an exponentially

138 ancement data enables us to obtain an atomic probability distribution map of the non-specific encount

139 quations that describe the time evolution of probability distribution moments.

140 a model in which neural activity encodes the probability distribution most consistent with a given im

141 considering parameter ranges and associated probability distribution obtained at any given transform

142 entropy of association is estimated from the probability distribution obtained by rigid rotation of a

143 sitivity distribution (SSDs) is a cumulative probability distribution of a chemical's toxicity measur

144 chain Monte Carlo samples from the posterior probability distribution of a generative model of the re

145 We derive an expression for the probability distribution of a given number of chance co-

146 human acoustical environment, shows that the probability distribution of amplitude-frequency combinat

147 We compute the probability distribution of cable lengths as a function

148 On the contrary, the probability distribution of caspase-3 activation for the

149 en chromatin factors and produce an accurate probability distribution of chromatin code.

150 Neural networks can efficiently encode the probability distribution of errors in an error correctin

151 o re-emphasize the importance of obtaining a probability distribution of fairly likely MSAs, instead

152 th what mean population rate, but not in the probability distribution of firing rates.

153 s, or rely on the assumption of a parametric probability distribution of gene measurements.

154 t the need of the assumption of a parametric probability distribution of gene measurements.

155 We present PRODIGEN (PRObability DIstribution of GEne Networks), a web-based

156 quence can be produced in multiple ways, the probability distribution of hidden recombination events

157 The probability distribution of hourly averages of B in the

158 In this work, we derive the probability distribution of interspecies covariance unde

159 te Carlo method for estimating the posterior probability distribution of model parameters.

160 ow how the CRIF shapes the form of the joint probability distribution of molecular copy numbers of th

161 TP production (P < 0.01), as well as reduced probability distribution of muscle movement forces compa

162 At long times, the probability distribution of NE is positively skewed and

163 Pioneering studies have shown that the probability distribution of opening length for a DNA hai

164 ances in a variety of circumstances from the probability distribution of physical distances.

165 d FHC R58Q and D166V hearts by analyzing the probability distribution of polarized fluorescence inten

166 ty estimation to generate a dataset-specific probability distribution of random background signal.

167 t a method that allows us to reconstruct the probability distribution of rate constants from decay da

168 cally, the same neuronal response; i.e., the probability distribution of sensory neuron firing rates

169 The probability distribution of spikes and seizures were not

170 ation theoretic approaches requires the full probability distribution of stimuli and response.

171 We show that the probability distribution of strength of the representati

172 We express the experimentally accessible probability distribution of the copy number of the gene

173 The probability distribution of the distance between the ini

174 ted by negativities in the phase-space quasi-probability distribution of the effective collective mod

175 d Bayesian methods to estimate the posterior probability distribution of the effectiveness of vesicoa

176 qualitatively and quantitatively affect the probability distribution of the gene product.

177 to the gorge, again we observe a two-peaked probability distribution of the gorge width.

178 um population density and all moments of the probability distribution of the habitat quality of occup

179 the model is able to reproduce the observed probability distribution of the Jaccard similarity index

180 ingly, the model can also predict the actual probability distribution of the Jaccard similarity index

181 n the basis of these findings, we obtain the probability distribution of the level of divergence betw

182 lso be re-expressed in terms of a functional probability distribution of the neuron density.

183 ifference DeltaF between two states from the probability distribution of the nonequilibrium work W do

184 d an explicit expression for the conditional probability distribution of the number of binding sites

185 a branching process model, we calculate the probability distribution of the number of copies of A on

186 Previously, the probability distribution of the number of DSBs has been

187 We compute the probability distribution of the number of mutations shar

188 peak deconvolution by restricting the prior probability distribution of the peak position in a model

189 f every pixel in the scene) to show that the probability distribution of the possible locations of li

190 ception of visual space is determined by the probability distribution of the possible real-world sour

191 e, systems) is compared with the equilibrium probability distribution of the spin overlap for finite

192 Dynamic territories emerge but the probability distribution of the territory border locatio

193 ntropy of association is calculated from the probability distribution of the translational and rotati

194 elative amount of molecules adsorbed and the probability distribution of their displacements over spa

195 case, we identify the functional form of the probability distribution of time elapsing until invasion

196 wds, assemblies of grains, and colloids- the probability distribution of time lapses between the pass

197 set of samples chosen from the a posteriori probability distribution of transcription factor binding

198 basin structure lead to a power law for the probability distribution of transpiration from a randoml

199 ation of phylogeny is based on the posterior probability distribution of trees.

200 n pulse-time set, generate a sample from the probability distribution of unknown underlying hormone s

201 ed using a matrix method for calculating the probability distribution of variant frequencies at sites

202 d over the course of a match there will be a probability distribution of velocities.

203 f the Jarzynski estimator for all N when the probability distribution of work values is Gaussian, as

204 ximation accurately capture the steady-state probability distributions of all components of these rea

205 The investigation was based on probability distributions of apparent activation energy

206 DY compares two conditions by evaluating the probability distributions of dependency networks from ge

207 bal average temperature metrics for DAI with probability distributions of future climate change produ

208 e Change assessment of climate impacts, onto probability distributions of future climate change produ

209 t's life history with published estimates of probability distributions of incubation period and age a

210 r of transmission eigenvalues determines the probability distributions of intensity and total transmi

211 d flexibility of compstatin, one-dimensional probability distributions of intrapharmacophore point di

212 We first created spatially explicit probability distributions of its candidate reservoir spe

213 mental results required models with distinct probability distributions of local defect concentrations

214 e described, which develop equations for the probability distributions of macroscopic state variables

215 Posterior probability distributions of model parameters provide bo

216 We also evaluate the probability distributions of pixel intensities in fluore

217 a-tRNA species into amino acids provides the probability distributions of possible amino acids into w

218 circuits allow us to sample from the output probability distributions of quantum walks on circulant

219 Comparison with summed probability distributions of radiocarbon dates from arch

220 nearly on a measure of similarity, but allow probability distributions of ratings to depend freely on

221 he mathematical variance of binary symmetric probability distributions of reward magnitudes; value wa

222 ion rate on applied force was obtained using probability distributions of rupture forces collected at

223 t provide quantitative information about the probability distributions of secondary-structure element

224 On the basis of these conformers, probability distributions of selected distances and angl

225 s and based future projections on downscaled probability distributions of the daily maximum temperatu

226 A Bayesian analysis was used to determine probability distributions of the parameter values of a m

227 1,600 natural images, we analyzed the joint probability distributions of the physical variables most

228 ajor variants are correctly predicted by the probability distributions of the possible physical sourc

229 Here we show that the probability distributions of the possible real-world sou

230 g a statistical function which describes the probability distributions of the prevalences of infectio

231 both the ground-state and the excited-state probability distributions of the resulting artificial mo

232 quality of occupied sites, and relating the probability distributions of total habitat quality and o

233 Finally, the anomalous probability distributions of tracer displacements become

234 zed algorithm whereupon the kernel induces a probability distribution on its set of partitions, where

235 ch novelties happen (Heaps' law) and for the probability distribution on the space explored (Zipf's l

236 oothing timescale and the width of the prior probability distribution on the space of models.

237 out the sample partition is represented by a probability distribution on the space of possible sample

238 se are two distinct cases that differ in the probability distribution on which the statistical test i

239 structures can be defined and computed, and probability distributions on spaces of such structures c

240 l cognitive processes require inference of a probability distribution (or "belief distribution") over

241 , or to sample paths according to an implied probability distribution, or as the second stage of a fo

242 Amino acid sequence probability distributions, or profiles, have been used s

243 spectral method for computation of the joint probability distribution over all species in a biologica

244 e tasked human participants with inferring a probability distribution over four possible latent cause

245 is to use Bayes' rule to compute a posterior probability distribution over latent causes.

246 a linear Markov network, and so, to a joint probability distribution over sequences, computable in l

247 Our coupled mixture model defines a prior probability distribution over the component to which a p

248 not encode just a single value but an entire probability distribution over the stimulus.

249 e made as a stochastic choice: That is, as a probability distribution over two options in a set, the

250 Probability distributions over external states (priors)

251 served to refer to the encoding of all other probability distributions over sensory and cognitive var

252 lysis tool for the systematic exploration of probability distributions over simulation time and state

253 pulations of neurons automatically represent probability distributions over the stimulus, a type of c

254 These results hold for arbitrary probability distributions over the stimulus, for tuning

255 thm iteratively samples from the conditional probability distributions P(Structure | Alignment) and P

256 Measuring distances between probability distributions permits a multivariate rather

257 Probability distributions play a central role in mathema

258 Unusual probability distribution profiles, including transient m

259 The representation of network nodes as probability distributions provides an efficient visualiz

260 The 99(th) percentiles of the window period probability distribution ranged from 44 days for laborat

261 ing scale, and kinetic models which assume a probability distribution rather than derive it from the

262 nerative model-based analysis, we found that probability distributions reflecting sensory uncertainty

263 A single joint probability distribution relates the values of regular a

264 However, it is unclear which probability distribution should be used to describe how

265 riation are often sparse, it is unclear what probability distribution should be used to describe the

266 d to the actual mutation times by calculable probability distributions, similar to the selection coef

267 tatistical approach gives skewed and complex probability distributions (single mode, 10 cm, at 2100;

268 capture the time-varying characteristics of probability distributions: spaghetti plots over one dime

269 Our shape signatures are just these probability distributions, stored as histograms.

270 elers consider heavy-tailed, downward-skewed probability distributions, such as the skewed Student [F

271 that spikes and seizures demonstrate similar probability distributions suggests they are not wholly i

272 e disorder was compared by using multinomial probability distribution tests.

273 ter affords a quasi-continuous hydrogen-only probability distribution that conveys immediate informat

274 re is described by an over-dispersed Poisson probability distribution that is consistent with heterog

275 blem by using Bayesian inference to derive a probability distribution that represents both the unknow

276 otein on other proteins is modeled using the probability distribution that the series of interactions

277 volution along a separatrix and non-Gaussian probability distributions that are measured to be in goo

278 ong ecologically relevant quantities and the probability distributions that characterize their occurr

279 imum entropy models are the least structured probability distributions that exactly reproduce a chose

280 mation about particularly important types of probability distributions, the populations of secondary

281 ta is sampled from the appropriate posterior probability distribution, then a coalescent genealogy is

282 We integrate the step-size probability distribution to obtain a version of the fluc

283 PeaKDEck uses this probability distribution to select an appropriate read d

284 tion collected in the wiki, we then assigned probability distributions to all parameters of the model

285 arning rules.Behavioural tasks often require probability distributions to be inferred about task spec

286 factorization method (5 options), choice of probability distributions to compare (3 x 4 options) and

287 ions were analyzed in the form of cumulative probability distributions to describe key risk-related f

288 tic models which were further improved using probability distributions to generate high-resolution ti

289 anagement of Multivessel Disease) with prior probability distributions to show how strongly we should

290 process adapting results from 'first passage probability distribution' to summarize statistics of ens

291 Higher-order cumulants of the probability distribution underlying the stochastic event

292 Interpreting the probability distributions using information theory, we s

293 , they can be precisely described by a known probability distribution-Wachter's MANOVA (multivariate

294 Using probability distributions, we varied the value of factor

295 We show that our method can give the correct probability distribution when alkylation events are rela

296 dence accumulation encode, on every trial, a probability distribution which predicts the animal's per

297 stead, for each configuration we calculate a probability distribution, which has a domain that encomp

298 the magnetic switching field decreases, its probability distribution widens, while the temperature o

299 m walks, the step lengths of which come from probability distributions with heavy power-law tails, su

300 nd vectors, but instead appears to represent probability distributions with the firing rates of popul