ライフサイエンスコーパス: Gaussian distribution

1 presented by probability distributions (e.g. Gaussian distribution).

2 is related to the symmetrical nature of the Gaussian distribution.

3 sholds for the individual T cells followed a Gaussian distribution.

4 e with the Debye-Waller theory including the Gaussian distribution.

5 e uncertainties that are assumed to follow a Gaussian distribution.

6 rent datasets that was well-described with a Gaussian distribution.

7 ter-pulse intervals in EDA follow an inverse Gaussian distribution.

8 m that models LD using a simple multivariate Gaussian distribution.

9 narrow size distribution and agree with the gaussian distribution.

10 cal analyses because the data did not follow Gaussian distribution.

11 ence procedures assume the data arise from a Gaussian distribution.

12 -tone sounds with frequencies sampled from a Gaussian distribution.

13 and ISI distributions that match the inverse Gaussian distribution.

14 ciations was consistent with a null-centered Gaussian distribution.

15 ecules in rigor were represented by a single Gaussian distribution.

16 nces (ILD) rapidly fluctuated according to a Gaussian distribution.

17 al limit theorems that give convergence to a Gaussian distribution.

18 hourly averages of B in the heliosheath is a Gaussian distribution.

19 and target zone center was well fitted by a Gaussian distribution.

20 s of the peptide layers was about 10 A for a Gaussian distribution.

21 n that was well modelled as a mixture of two Gaussian distributions.

22 y tails that are effectively modeled using q-Gaussian distributions.

23 ow that it also performs excellently for non-Gaussian distributions.

24 ior can be described in terms of independent Gaussian distributions.

25 method to address highly overlapping and non-Gaussian distributions.

26 t variation in blood-pool and liver SUVs had gaussian distributions.

27 uilibrium (denoted I(eqm)) are fitted by two Gaussian distributions.

28 current pulses with amplitudes drawn from a Gaussian distribution (10-100 pA standard deviation) to

29 The width of the Gaussian distribution, a measure of the diameter of the

30 Using a model of a Gaussian distribution about the average torsion angles t

31 st phenotypic variation-resulting in normal (Gaussian) distributions across populations.

32 ientation distribution function, including a Gaussian distribution and a formula based on the maximum

33 eter recovery from data generated from an ex-Gaussian distribution and from a Ratcliff Diffusion Mode

34 n angle distribution function deduced by the Gaussian distribution and the maximum entropy distributi

35 orov-Smirnov-distance between a hypothetical Gaussian distribution and the observed distribution of t

36 le (rv) was generated by randomly sampling a Gaussian distribution and used as a benchmark to compare

37 is then modeled as a mixture of multivariate gaussian distributions and fitted through a k-means algo

38 d in C code the Bayesian error estimator for Gaussian distributions and normal-inverse-Wishart priors

39 ciently separated to be independent, exhibit Gaussian distributions and provide mean-squared fluctuat

40 at the underlying startle response has a non-Gaussian distribution, and that the traditional PPI metr

41 ive mixtures model statistical analysis, two Gaussian distributions appeared to comprise the total GC

42 They formed a Gaussian distribution around a mean between 34 and 35, a

43 mental background noise is shown to follow a Gaussian distribution at all wavelengths, and a method i

44 e a robust yield of 90% and percentage obeys Gaussian distribution at various stages.

45 more scalable sampling scheme for truncated Gaussian distributions, based on a Hamiltonian Monte-Car

46 l gene expression data sets fit multivariate Gaussian distributions both before and after subjecting

47 symptoms and diagnosis were shown to have a Gaussian distribution, but were not useful predictors of

48 stics consistent with the background noise's Gaussian distribution, common to all wavelengths.

49 smium isotopic data form a wide, essentially gaussian distribution, demonstrating that, with respect

50 ally normal immediately after dilation, this gaussian distribution disappeared during the follow-up p

51 nated seeds, bacteria are distributed in non-Gaussian distributions, e.g., a lognormal distribution.

52 This method utilizes a grayscale Gaussian distribution effect to model inaccuracies inher

53 ults was controlled and validated by a mixed Gaussian distribution estimation method.

54 ImpG-Summary/LD), that assume a multivariate Gaussian distribution for the association summary statis

55 rithm is the use of an iteratively optimized Gaussian distribution for the selection of trial distanc

56 The DEER data were analyzed assuming Gaussian distributions for discrete populations of spins

57 The data are consistent with independent Gaussian distributions for each mode.

58 n bio-basis function neural network with two Gaussian distributions for model parameters (weights) pe

59 ffects is known to be well approximated by a Gaussian distribution from previous empirical fits.

60 model can effectively learn low-dimensional Gaussian distributions from the original high-dimensiona

61 Assuming a Gaussian distribution function, a physisorbed stilbene d

62 terms of a superposition of two-dimensional Gaussian distribution functions in the Ramachandran spac

63 led as two different independent generalized Gaussian distribution functions, representing, respectiv

64 ereas interpretation of the same data with a Gaussian distribution gives a result that is systematica

65 However, serotonin release exhibits two Gaussian distributions: higher frequency of small releas

66 In healthy children, CDR3 lengths displayed Gaussian distribution in both CD45RA and CD45RO subsets.

67 itude distribution that was well fitted by a Gaussian distribution in four out of five cases.

68 pression, there was rapid reestablishment of Gaussian distributions in CD45RA cells.

69 ons that were obtained fit quite well to the Gaussian distribution indicating no high- or low-mass di

70 s in isolated cell-derived EVs follow a wide Gaussian distribution, indicating the presence of a rang

71 Rather, the data suggested a Gaussian distribution indicative of stochastic protein d

72 ibing the location of each protein atom by a Gaussian distribution instead of a fixed position based

73 ribution are quite similar, showing that the Gaussian distribution is a good approximation for the an

74 spur), where the hollowing out of an initial Gaussian distribution is observed, in line with previous

75 After assessment for Gaussian distribution, mean and standard deviation (SD)

76 analysis of the donor decay profiles using a Gaussian distribution model.

77 The intrinsic specificity obeys a Gaussian distribution near the mean and an exponential d

78 The standard deviation in the inferred Gaussian distribution of activation energies, computed f

79 site effects in the solid-state modeled by a Gaussian distribution of activation energies.

80 ons of a protein described as a multivariate Gaussian distribution of atomic displacements and compar

81 The normal 476-bp DNA fragment exhibited a Gaussian distribution of bend angles centered at 0 degre

82 ved distribution appears inconsistent with a Gaussian distribution of binding energies.

83 t was performed depending on Gaussian or non-Gaussian distribution of data.

84 h can be described using a model involving a Gaussian distribution of distances with an average dista

85 ton delocalization and can be described by a Gaussian distribution of energies with a width sigma=0.1

86 Using these criteria, a Gaussian distribution of fluorescence lifetimes satisfac

87 We show that a Gaussian distribution of heteropolymer segments, coupled

88 cement of a 150-nm-diameter particle and non-Gaussian distribution of increments.

89 neities are responsible for the generic, non-Gaussian distribution of increments.

90 bilayer surfaces are uncorrelated, yielding Gaussian distribution of instantaneous widths of the mem

91 iscrete lifetime at 15.0 ns (free COP) and a Gaussian distribution of lifetimes centered at 2.8 ns (r

92 All three molecules display a Gaussian distribution of lifetimes, consistent with an e

93 rn, and a model that implements a 0-inflated Gaussian distribution of mean group abundance for each t

94 Here we describe the non-Gaussian distribution of measured distances that is the

95 ed by most random walk models that predict a Gaussian distribution of membrane potential.

96 aller than the focused laser beam leads to a Gaussian distribution of single molecule fluorescence in

97 Assuming a Gaussian distribution of the 15N CSA values, the mean an

98 tandard deviation, [Formula: see text], of a Gaussian distribution of the orientation of the easy-mag

99 We therefore assume a Gaussian distribution of the thresholds, which is simple

100 stances in the embryo, and departures from a Gaussian distribution of these fluctuations.

101 The non-Gaussian distribution of this data affects identificatio

102 imes, which is responsible for the canonical Gaussian distribution of timing behavior.

103 all the DNA in a step-wise fashion to give a Gaussian distribution of topoisomers, demonstrating a sw

104 lyclonal T cell repertoire demonstrated by a Gaussian distribution of V beta-specific peaks.

105 s, mSiO(2)/Pt/MCM-48 yields a C(28)-centered Gaussian distribution of waxy hydrocarbons from polyolef

106 Highly symmetric non-Gaussian distributions of CF support zero-sum dynamics.

107 ion intensity-dependent method to check for Gaussian distributions of ion series and an ion intensit

108 The previously reported modal or Gaussian distributions of sparks detected by eye must th

109 nalog models to the discrete and continuous (Gaussian) distributions of a single proton binding-disso

110 For each sample, BONOBO assumes a Gaussian distribution on the log-transformed centered ge

111 was processed using a He(2+) ion-beam with a Gaussian distribution or by exposure to ultraviolet/O3,

112 were often best fit with several single non-Gaussian distributions or mixtures of Gaussian distribut

113 n at all observed timescales rather than the Gaussian distribution predicted by the central limit the

114 le non-Gaussian distributions or mixtures of Gaussian distributions, rather than the more frequently

115 This mixing reduces the width of the gaussian distribution several times in comparison to the

116 es in behavioral tasks should naturally have Gaussian distributions, so that deviations from normalit

117 T, background signals are modeled by a local Gaussian distribution that is accurately estimated from

118 otational free energy barriers follow skewed-Gaussian distributions that are not altered significantl

119 The intensity encoding scheme utilizes the Gaussian distributions that characterize the relationshi

120 s describing the two independent generalized Gaussian distributions that underlie the WBQ chromatogra

121 The width of the Gaussian distribution, the variability of a spatial rest

122 Assuming the varphi angles follow a Gaussian distribution, the width of this distribution ca

123 Unlike the gaussian distribution, this model provided a good repres

124 alculated for each scan by fitting a bimodal gaussian distribution to the voxel-intensity histogram w

125 nge of different mean and standard deviation Gaussian distributions to test the validity of our appro

126 den Markov model (HMM) or a mixture model of Gaussian distributions, to find a set of distinct FC pat

127 that estimating MI of a bi- and tri-variate Gaussian distribution using k-nearest neighbor (kNN) MI

128 lations were refined in terms of anisotropic Gaussian distributions via least-squares minimization of

129 n function such as a delta-distribution or a Gaussian distribution was not adequate to describe the m

130 Inverse gaussian distributions were fitted to observed annual ra

131 a broader model set: the generalized inverse Gaussian distribution, which includes the inverse Gaussi

132 th, the centroid distribution converges to a Gaussian distribution whose mean and variance are determ

133 t in data that can be well-approximated by a Gaussian distribution whose mean and variance are determ

134 h characterized by an interlobe distance and Gaussian distribution width (disorder).

135 source of the mass spectrometer and follow a Gaussian distribution with a full width at half-maximum

136 ed from immature rats was best fitted with a Gaussian distribution with a mean of 6.95.

137 ('group 2', approximately 40%), R(c/p) had a Gaussian distribution with a mean value of 0.625.

138 alues for the cranium were randomized with a Gaussian distribution with either coefficients of variat

139 opic ML Procrustes problem assuming a matrix Gaussian distribution with factored covariances.

140 AFADs showed a gaussian distribution with mean of 16.3 A and standard d

141 e these assumptions since they come from non-Gaussian distributions with a non-trivial mean-variance

142 ipal orientations drawn from two categories: Gaussian distributions with different means and equal va

143 ure rats was best fitted with the sum of two Gaussian distributions with means of 6.68 and 7.32.