ライフサイエンスコーパス: random sampling

1 or both k-fold cross-validation and repeated random sampling.

2 s provide other useful functionalities, e.g. random sampling.

3 lected from birth certificates by stratified random sampling.

4 be consistently obtained by using localized random sampling.

5 te resampling, different-site resampling and random sampling.

6 g and regulating facilities using stratified random sampling.

7 e using ImageJ to perform systematic uniform random sampling.

8 to 3.5-fold greater than that expected from random sampling.

9 s (VDCs) from each district were selected by random sampling.

10 selected from the district using multi stage random sampling.

11 Eligible samples were selected using cluster random sampling.

12 t low-angle shot sequence is used with quasi-random sampling.

13 which households were selected by stratified random sampling.

14 habitats relative to the null hypothesis of random sampling.

15 es of active shRNAs up to 5-fold relative to random sampling.

16 ded into two groups: index and validation by random sampling.

17 ation spectroscopic-filtering with iterative random sampling (2D-COS-firs) is reported.

18 We used stratified random sampling (according to age, residence [urban vs r

19 cantly better when they were chosen with the random sampling algorithm.

20 iciently measure this quantity, we develop a random sampling algorithm.

21 importance sampling distribution and using a random sampling algorithm; however, selection of importa

22 Of the total random sampling analyses, 50% showed a highly statistica

23 With methodology based on random sampling and behavioural tests of genuineness, we

24 fold, namely decreasing genetic diversity by random sampling and leading to population-wide inbreedin

25 atum radiatum were analyzed using systematic random sampling and serial section analyses.

26 sections were sampled by systematic uniform random sampling and stained with Masson trichrome, and t

27 kends), (ii) completely random or stratified random sampling, and (iii) a number of sampling strategi

28 difference covariance matrix with iterative random sampling, and is capable of revealing contaminati

29 We used flux balance analysis, random sampling, and principal component analysis to exp

30 the laying sequence, the selection criteria, random sampling, and the duration and temperature of tra

31 Our analysis is based on a random sampling approach using real data sets from 16 pu

32 A stratified random sampling approach was used to enhance precision i

33 We conclude that random sampling artifact is very unlikely to be the expl

34 A random sampling assigned participants into group 1 (with

35 ified two-stage cluster sampling with simple random sampling at each stage for each stratum was used

36 . WebTool, a user-friendly online server for random sampling-based evaluation of distance significanc

37 In this article, we present a random-sampling-based statistical algorithm to identify

38 arated from the training set by a stratified random sampling before the analysis, was used to determi

39 use of museum records: first without initial random sampling, comparison with contemporary results ca

40 Subsequently, 42 subjects recruited from a random sampling cross-sectional study were analysed.

41 'almost unbiased' theorem similar to that of random-sampling cross-validation.

42 ion in 2001, 2006, and 2011, using a 2-stage random sampling design in 2 urban and 3 rural strata.

43 sis of hospital records, we used a two-stage random sampling design to create a nationally representa

44 We used a multistage random sampling design to generate a representative samp

45 ed when samples are collected using a simple random sampling design.

46 Using a multistage, random-sampling design with replacement, the Monitoring

47 UK was selected by a multi-stage, clustered, random-sampling design.

48 ssembly mechanisms may explain this pattern, random sampling effects can create this pattern through

49 our computer simulations show that these non-random sampling features may affect the topological info

50 erpart of UniCon3D that performs traditional random sampling for protein modeling aided by predicted

51 Control subjects were selected by stratified random sampling from 28,123 incident pancreatic cancers

52 Random sampling from a cohort of 5,928 subjects was perf

53 re composed for each procedure by stratified random sampling from a list of experts nominated by the

54 o histologic sections selected by systematic random sampling from four mice were immunostained and im

55 Participants were selected using stratified random sampling from general surgery residency programs

56 form a retroviral particle are determined by random sampling from the cell-and thus dictated by the c

57 In a random sampling from the unenhanced (n = 201) and Defini

58 s using a global sensitivity approach called Random Sampling High Dimensional Model Representation (R

59 This work presents an adapted Random Sampling - High Dimensional Model Representation

60 The Random Sampling-High Dimensional Model Representation (R

61 al sensitivity analysis (SA) method based on Random Sampling-High Dimensional Model Representation (R

62 ion using the recently developed approach of random sampling-high-dimensional model representation (R

63 This was in contrast to the impact of weekly random sampling (i.e., using saliva swabs) of at least 1

64 ations with higher accuracy than traditional random sampling in a small benchmark of 6 proteins; (ii)

65 74 adults who were selected using multistage random sampling in Gondar town, North West, Ethiopia.

66 sidue protein can find its native topomer by random sampling in just approximately 100 ms.

67 s to 1,521 physicians selected by stratified random sampling in the 1995 National Ambulatory Medical

68 he eligible subsets at each node by weighted random sampling instead of simple random sampling, with

69 Its superior performance over random sampling is demonstrated on secondary ion mass sp

70 advanced and able to overcome the under- and random-sampling issues of the current sequencing approac

71 While this is true for random sampling, it is not true with separate sampling,

72 A stratified, cluster-random sampling method was used to select students acros

73 e compare the uniformly-random and localized random sampling methods over a large space of sampling p

74 Combining a random sampling model with a terrageny generates numeric

75 compare different methodologies, we picked a random sampling of 100 nasopharyngeal specimens recovere

76 In a random sampling of 130 genes encoding secretory proteins

77 unds in a structure descriptor space so that random sampling of 20% of the whole data set produced an

78 A random sampling of 230 BACs indicated an average insert

79 ng of "super-emitters" that may be missed by random sampling of a subset of the total.

80 d of rare disease alleles substantially over random sampling of cases or controls or sampling based o

81 elop an algorithm for efficiently performing random sampling of causal graphs.

82 Random sampling of cDNAs from two evolutionarily diverge

83 east three orders of magnitude compared to a random sampling of compact folds.

84 Our method is based on random sampling of conformation space and subsequent loc

85 y native-like conformations mostly resort to random sampling of conformations to achieve computationa

86 matic sampling of cases (when necessary) and random sampling of controls will be implemented.

87 ng and gene dropping of genotype vectors and random sampling of each of the model parameters from the

88 ed from rotamer libraries, are combined with random sampling of explicit urea molecules in interactio

89 to account the special nature of these data: random sampling of genomic segments from one or more ind

90 We characterize these biases for random sampling of genotypes as well as samples drawn fr

91 comparable to those reported from a national random sampling of HIV-infected men and women receiving

92 ty in the assignment of genotypes because of random sampling of homologous base pairs in heterozygote

93 of state of Sao Paulo, using systematic and random sampling of households between March 2004 and Jul

94 Random sampling of ICU professionals from a directory.

95 Lunar meteorites represent a more random sampling of lunar material than the Apollo or Lun

96 nds, we recommend a size correction based on random sampling of modules when using biological process

97 Sequencing errors and random sampling of nucleotide types among sequencing rea

98 Overall, random sampling of only one lumen in CVCs causing CRBSI

99 field diversity was consistent with a nearly random sampling of orientation, spatial phase, and retin

100 ifurcation sets, numerical continuation, and random sampling of parameters.

101 also normally distributed, consistent with a random sampling of parental genes.

102 Stratified random sampling of patients from outpatient clinics was

103 ng with leave-one-out cross-validation, with random sampling of single sequences from individuals on

104 The PEROX model was developed using a random sampling of subjects in a derivation cohort (n=58

105 obability) is no more efficient than uniform random sampling of the entire population, because resour

106 Uniform random sampling of the steady-state flux space allows fo

107 We used k-fold cross validation and random sampling of the SVM classifier to assess the clas

108 each annotation of a test gene is derived by random sampling of the whole genome.

109 Random sampling of this cohort was performed, with appro

110 ers several years after war using consistent random sampling of war-affected people across several We

111 Regularized GGM coupled with iterative random samplings of genes was expanded into a network th

112 Data sets ascertained by random sampling often harbor cryptic relatedness that ca

113 Ne reflects the effect of random sampling on the genetic composition of a populati

114 ed in the laboratory for some generations by random sampling prior to artificial selection.

115 In the first stage, we used a simple random-sampling procedure stratified by economic-geograp

116 We expect that the localized random sampling protocol helps to explain the evolutiona

117 theory demonstrates that by using uniformly-random sampling, rather than uniformly-spaced sampling,

118 ly selected 150 for the study using a simple random sampling routine in Stata.

119 nt algorithms for search space size, uniform random sampling, segment placement probabilities, mean,

120 and compares favorably with a conventional, random sampling, semiquantitative method.

121 incide with histone acetylation islands, and random sampling shows that 33% (13/39) of these can func

122 ion and validation data sets by using simple random sampling stratified by sex, BMI category, and age

123 ited 100 homeless persons using a stratified random sampling technique from January to March 2014.

124 A systematic random sampling technique was used to select 359 study p

125 Simple random sampling techniques were used to select a subset

126 week and had better accuracy than stratified random sampling techniques.

127 tative sites (Chiri, C, and Wabero, W) using random sampling techniques.

128 The method of random sampling that was used was comparable with linear

129 eoarthritis Project, using stratified simple random sampling to achieve balance according to radiogra

130 hone dialing who were selected by stratified random sampling to approximate the age, sex, and county

131 of existing motif-finding tools by employing random sampling to effectively remove non-motif-containi

132 This cross-sectional study used multistage random sampling to enroll 1,134 12-year-old schoolchildr

133 of this organism, we conducted a systematic random sampling to identify 3,000 nasopharyngeal swab sp

134 ased, observational study, we used two-phase random sampling to recruit adults with disabilities and

135 number of sequence combinations makes wholly random sampling unfeasible, two key simplifications may

136 Random sampling was the least biased method.

137 Multistage, cluster random sampling was used to select a nationally represen

138 Linear programming and uniform random sampling were applied herein to identify candidat

139 logical receptive field structure, localized random sampling, which yields significantly improved CS

140 Multistage stratified cluster random sampling with probability-proportional-to-size pr

141 mples achieved either through bootstrapping (random sampling with replacement) or subsampling (random

142 Cluster random samplings with probability proportionate to size

143 y weighted random sampling instead of simple random sampling, with the weights tilted in favor of the

144 on carried by each neuron arises purely from random sampling within the stimulus space.

145 m sampling with replacement) or subsampling (random sampling without replacement) on learning data.

146 statistically sufficient to explain TL under random sampling, without the intervention of any biologi