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

1 resent statistical samples from the inferred probability distribution.

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

3 we describe each experimental condition by a probability distribution.

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

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

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

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

8 etation of this simple and clean exponential probability distribution.

9 ility distribution, a quantum extension of a probability distribution.

10 utions according to this dynamically-derived probability distribution.

11 ing based on neighbor-dependent Ramachandran probability distributions.

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

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

14 configurations inconsistent with the target probability distributions.

15 oises could be strengthened with more robust probability distributions.

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

17 their conformational properties in terms of probability distributions.

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

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

20 a mixture of several discrete or continuous probability distributions.

21 tribution consisting of log normal and gamma probability distributions.

22 egimes, we present the concept of eigenvalue probability distributions.

23 elevant variables, rather than on their full probability distributions.

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

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

26 rtical population activity as the width of a probability distribution, a hypothesis that lies at the

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

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

29 xpression and additionally provides the full probability distribution and credible intervals for each

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

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

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

33 We study the concomitant probability distribution and show that, when varying the

34 gate structure and describe their morphology probability distribution and spatial distribution.

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

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

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

38 nt well-known random network models and edge probability distributions and demonstrate that probabili

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 ype-II topoisomerases in terms of stationary probability distributions and probability currents on th

42 can represent both the complex, multivariate probability distributions and the causal pathways influe

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

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

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

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

47 This suggests a probability distribution approximating an inverse power-

48 Posterior probability distributions are constructed for all model

49 or the original MICI study and show that the probability distributions are skewed towards lower value

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

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

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

53 tal divergence, the distance between 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 en used, but we hypothesized that continuous probability distributions (CPD) of decay rates can descr

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

59 More fundamentally, our results suggest that probability distributions decoded from human visual cort

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

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

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

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

64 Best fitting probability distributions differed among the carnivores

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

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

67 rsity, investigating four different disorder probability distributions (DPDs) ranging from the case o

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

69 wards not as a single mean, but instead as a probability distribution, effectively representing multi

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

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

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

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

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

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

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

77 mic equilibrium that establishes a G1 length probability distribution for a population of hESCs and p

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

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

80 The model recovers the probability distribution for cone fate patterning in the

81 The posterior probability distribution for selection coefficients is c

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

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

84 ave a parameterized model with an underlying probability distribution for the estimator, making it di

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

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

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

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

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

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

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

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

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

94 Specifically, we calculate probability distributions for microscopic density fluctu

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

96 SubSynMAP generates probability distributions for that reveal the functional

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

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

99 We decoded probability distributions from population-level activity

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

101 titioned according to a bivariate log-normal probability distribution function (PDF) of carbon and wa

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

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

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

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

106 itative analysis of REES data using Gaussian probability distribution function clearly indicates that

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

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

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

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

111 y sampling the parameter values from a joint probability distribution function.

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

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

114 ime-to-event data were fitted by exponential probability distribution functions computed using maximu

115 Modeling using different probability distribution functions showed that MA'AT mod

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

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

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

119 ession via neural network ensembles to learn probability distributions functions (pdfs) that describe

120 Probability distributions having power-law tails are obs

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

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

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

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

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

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

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

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

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 With discrete probability distributions it is not possible to specify

134 From this conditional probability distribution, it is shown that when the cent

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 Spatial probability distribution mapping identified a threshold

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

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

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

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 two microtubule-binding domains, the angular probability distribution of a single microtubule-binding

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

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

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

149 The output is both a posterior probability distribution of emitter locations that inclu

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 A method for measuring the size and size probability distribution of free volume regions in polym

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

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

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

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

158 esent a method for determining the posterior probability distribution of IBD segment endpoints.

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

160 e we present the first exact analysis of the probability distribution of LRS for species described by

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

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

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

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

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 NDA method was comparable with the estimated probability distribution of SF, yielding similar estimat

170 The probability distribution of spikes and seizures were not

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

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

173 ancer evolution and derive a formula for the probability distribution of the cancer cell frequency of

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

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

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

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

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

179 istance to the first branching point and the probability distribution of the intensity.

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

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

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

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

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

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

186 m, and derive expressions for the stationary probability distribution of the number of mating types,

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

188 ithm that generates the support of the joint probability distribution of the occupancy spectrum; comp

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

190 These include the probability distribution of the separation vector betwee

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

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

197 fuzzy binding in terms of the entropy of the probability distribution of transitions towards decreasi

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

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

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

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

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

203 We compute analytically the probability distributions of filament lengths for both s

204 esian inference techniques, we determine the probability distributions of global Se emissions from th

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

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

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

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

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

210 mputing Jensen-Shannon distances between the probability distributions of methylation in a test and a

211 Posterior probability distributions of model parameters provide bo

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

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

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

215 Comparison with summed probability distributions of radiocarbon dates from arch

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

217 atively weight and combine ESMs and estimate probability distributions of return levels.

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

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

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

221 rences between these groups, each of the two probability distributions of swimming speed are accurate

222 We also compared the probability distributions of temporal variations of conn

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

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

225 1,600 natural images, we analyzed the joint probability distributions of the physical variables most

226 we identify the differences in two-electron probability distributions of the prevailing NSDI pathway

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

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

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

230 Finally, the anomalous probability distributions of tracer displacements become

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

232 ware system that calculates the a posteriori probability distribution on the number of contributors.

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

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

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

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

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

238 cale behavior quantified by the displacement probability distribution or the turning angle distributi

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

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

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

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

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

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

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

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

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

248 The output of DeepH3 is a set of probability distributions over distances and orientation

249 Probability distributions over external states (priors)

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

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

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

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

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

255 Measuring distances between probability distributions permits a multivariate rather

256 Probability distributions play a central role in mathema

257 Unusual probability distribution profiles, including transient m

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

259 resented in brain activity as the width of a probability distribution, providing critical evidence fo

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

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

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

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

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

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

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

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

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

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

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

274 nformation about heterogeneous clusters into probability distributions that can be described using si

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

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

277 derive analytical results for time-dependent probability distributions that provide insights into the

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

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

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

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

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

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

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

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

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

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

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

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

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

291 probe molecule, the free volume element size probability distribution was determined and found to be

292 Using probability distributions, we varied the value of factor

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

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

295 erse Gaussian; and the gamma and exponential probability distributions which have lighter tails (high

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

297 om repeated experiments sample the resulting probability distribution, which we verify using classica

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