ライフサイエンスコーパス: number of experiment

1 pling variability(3,6,7) necessitate a large number of experiments.

2 refine the inferred relations with a limited number of experiments.

3 fective multidrug combinations using a small number of experiments.

4 esign analysis was carried out to reduce the number of experiments.

5 the experimental conditions using a smaller number of experiments.

6 a when the number of TFs is greater than the number of experiments.

7 compatible with high levels in a significant number of experiments.

8 e, translating to a sixfold reduction in the number of experiments.

9 heology of a complex fluid through a limited number of experiments.

10 ination drug screens with a relatively small number of experiments.

11 ccessfully map this phase space in a minimal number of experiments.

12 dels for any organism from relatively modest numbers of experiments.

13 8) was greatly reduced from the actual total number of experiments (1722), which minimized the worklo

14 ered site potentials have been explored in a number of experiments, a more general, dynamical control

15 heories about population coding and keep the number of experiments and animals to a minimum.

16 th existing setups, and reduces the required number of experiments and animals.

17 col, enabling accurate modeling with limited number of experiments and at an unprecedented rate.

18 neck or inbreeding is supported by a growing number of experiments and is explained theoretically by

19 ll help to interpret and analyze the growing number of experiments and simulations dealing with cryst

20 ansfer in DNA over a distance >4 nm, a large number of experiments and theories have been advanced in

21 ing in both average optimization efficiency (number of experiments) and consistency (variance of outc

22 A number of experiments are suggested that would provide a

23 The number of experiments based on sequencing technologies,

24 rks depends on the size of the dataset (i.e. number of experiments), but this dependence is different

25 mization algorithm(10,11), which reduces the number of experiments by balancing exploration and explo

26 ulting in optimized separations in a limited number of experiments by optimizing the gradient slope.

27 our methodology in combination with a small number of experiments can be used to predict the yield o

28 ne when applied topically but because of the number of experiments carried out a comparison between t

29 of the predictions, which require a minimal number of experiments compared to the traditional one-at

30 A number of experiments conducted to demonstrate the obser

31 etwork that could explain the data, when the number of experiments does not allow identification of u

32 We successfully tested PathFinder with a number of experiments, e.g. the well studied glycolysis

33 Although a number of experiments failed to define a role for ElrA i

34 However, a growing number of experiments find limited temperature dependenc

35 We simulate a number of experiments from the literature at both the ce

36 the method to handle the case when a certain number of experiments, from several species close to the

37 ng all combinations is difficult because the number of experiments grows exponentially with the numbe

38 Since this discovery, an overwhelming number of experiments have been conducted to further def

39 In the context of quantum magnetism, a number of experiments have demonstrated the feasibility

40 remain to be clearly defined, an increasing number of experiments have implicated the generation of

41 ology of natural variation, as a substantial number of experiments have resulted in a valuable amount

42 A large number of experiments have since exploited the Brownian

43 ocesses are not fully understood; however, a number of experiments have suggested that peripheral tol

44 ombined with results from a relatively small number of experiments, have provided limited mechanistic

45 Finally, a limited number of experiments implicate that cAMP activates the

46 rameters without the need to perform a large number of experiments in the laboratory.

47 An increasing number of experiments investigate the properties of fitn

48 omplete gene expression profiles for a large number of experiments is costly.

49 In a growing number of experiments, it is important to characterize t

50 o high information content while keeping the number of experiments low.

51 line described enables the prediction of the number of experiments needed for an acceptable collapse

52 uired experimental sampling and estimate the number of experiments needed to "complete" a particular

53 active learning has been shown to reduce the number of experiments needed to obtain high-confidence p

54 uracy of matrix completion itself and in the number of experiments needed to train an accurate predic

55 the accelerated phase targeting in a minimum number of experiments of klockmannite CuSe, which could

56 By comparing our results to a number of experiments on controlled migration through po

57 he past decade, there has been an increasing number of experiments on spontaneous Bose coherence of e

58 and gradient method optimization: a minimum number of experiments or design of experiments (DoE) is

59 ere investigated using FFD which reduced the number of experiments performed by identifying 720 key e

60 With an increasing number of experiments performed under a general and mult

61 The task of weighing solids for large numbers of experiments poses a bottleneck for screening

62 e signal components was limited to the total number of experiments rather than the total number of bi

63 lations reported here agree very well with a number of experiments reported previously.

64 alytic rate laws from only a fraction of the number of experiments required in classical kinetic meas

65 The number of experiments required to arrive at optimal comp

66 Yet, for most ecological systems, the number of experiments required to build, model or analys

67 Next, it is shown that the number of experiments required to characterize a complex

68 set of experiments, and, what is the minimum number of experiments required to characterize the syste

69 lity to find optimal configurations, and the number of experiments required to find the optimum.

70 ta and results in substantial savings in the number of experiments required to make accurate drug-tar

71 Both parameters determine the number of experiments required to obtain meaningful resu

72 confidence limits, which, for a fixed total number of experiments, returns the optimal number of rep

73 vidence for this is strong and compelling, a number of experiments reveal a role for the superior col

74 A number of experiments show that the approximately 3 nm A

75 e shown to enhance fiber excitability, and a number of experiments show that this is a direct effect

76 elf-consistent framework for understanding a number of experiments, shows that the energy landscape o

77 A number of experiments suggested that these effects were

78 covering useful cocrystals and decreases the number of experiments that are needed by selecting API:g

79 oratory techniques has greatly increased the number of experiments that can be carried out in the che

80 umulatively, these three factors limited the number of experiments that could be repeated.

81 els can provide a compact summary of a large number of experiments that led to mechanism formulation

82 inhibitor concentrations, reducing the total number of experiments that would normally be needed.

83 take ~1-2 d, depending on the sample and the number of experiments to be processed.

84 d performance of this scheme, we conducted a number of experiments to evaluate its reliability and la

85 However, this approach requires a large number of experiments to identify both the composition a

86 In this study, we performed a number of experiments to investigate the actions of NPY

87 e data acquired, thus requiring an increased number of experiments to obtain sufficient kinetic infor

88 approach that uses the results of a limited number of experiments to predict the outcomes (coexisten

89 Lastly, we propose a number of experiments to verify the existence and quanti

90 A limited number of experiments under in vivo conditions also demo

91 analysis is thus roughly proportional to the number of experiments, underscoring the need for minimiz

92 curve approximately 0.71), the dependency on number of experiments used is nearly identical to that p

93 The number of experiments usually is much smaller than the n

94 Despite the large number of experiments, we identified several gaps in the

95 By conducting a large number of experiments, we prove that the proposed PCA-MD

96 acy, linearity, sensitivity, selectivity), a number of experiments were performed to specifically dem

97 be optimized with high accuracy and a lower number of experiments when compared with the classical u

98 fective experimental conditions in a limited number of experiments, which allowed us to prepare the n

99 should make it possible to undertake a large number of experiments with MSCs in transgenic mice that