ライフサイエンスコーパス: a posteriori

1 accurate by incorporating experimental data a posteriori.

2 Here, the former is addressed a posteriori.

3 ation (3DOSEM) and the 3-dimensional maximum a posteriori (3DMAP).

4 The a posteriori accuracy of the predictions suggests the me

5 Indeed, in an a posteriori analysis, the normal weightlifters proved c

6 ility to over-fitting by adopting a Bayesian a posteriori approach based on a Laplacian prior in para

7 Secondary end points included: a posteriori assessment of the accuracy of the infectiou

8 The application of a maximum-a-posteriori Bayesian inference method identified a line

9 e chain, a prediction that could be verified a posteriori by the high-resolution crystal structure of

10 A posteriori comparisons indicate that, in the first-cen

11 A posteriori-corrected discriminant analysis was able to

12 Our straightforward "a posteriori" correction yields clean linear images as c

13 ods (equal weights, literature review-based, a posteriori data-based, and weights based on Bayesian a

14 s integration, we used nonparametric maximum a posteriori decoding to compare the ability of neurons

15 st study to investigate associations between a posteriori-derived DP and retinal vessel caliber.

16 tor, and the Dutch Healthy Diet index] and 2 a posteriori dietary patterns.

17 tau 2)], and use Bayesian analysis to obtain a posteriori distribution of mu in terms of the data.

18 utions of the Smoluchowski equation based on a posteriori error estimates.

19 l (WTA) models and a Bayesian model, maximum a posteriori estimate (MAP), to determine which predicte

20 We calculated maximum a posteriori estimates of song spectrograms using a gene

21 otential functions in the MRF so its maximum a posteriori estimation can be reduced to the well-known

22 Further, as an extension, maximum a posteriori estimation is provided.

23 to segment the minimum distance and maximum a posteriori estimation to infer de novo CNVs from the s

24 Coupled with segmentation and maximum a posteriori estimation, our algorithm compares favorabl

25 s at robustness by using a priorless maximum a posteriori estimator and at efficiency by a dynamic pr

26 Quantitative analysis ruled out a posteriori explanations for the vesicles with low rele

27 pH sensors that can be efficiently modified a posteriori for specific applications.

28 and used to construct coexpression networks a posteriori, for which regulators were predicted based

29 eneration consortia efforts, which comprised a posteriori harmonization of exposure data and the incl

30 sion (blood flow) were essentially evaluated a posteriori, i.e. after generating a hollow network, bl

31 o analyze the parametric behavior of maximum a posteriori inference calculations for graphical models

32 A posteriori, it turned out that the patients in these t

33 s which targets to interrogate offline using a posteriori knowledge such as prior observation, identi

34 del alleviates the drawbacks of MAP (maximum a posteriori log likelihood) scores.

35 tion and a two-dimensional iterative maximum a posteriori (MAP) algorithm using attenuation correctio

36 tion process of parameters through a maximum a posteriori (MAP) Bayesian method to facilitate the met

37 We obtained very high Maximum a Posteriori (MAP) classification with a mixture of 12 d

38 Maximum a posteriori (MAP) common secondary structures, sequence

39 the time-frequency plane that yield maximum a posteriori (MAP) spectral estimates that are continuou

40 tructed with the fully 3-dimensional maximum a posteriori method, and CT images were reconstructed wi

41 with 2 hybrid methods with those obtained by a posteriori methods and compare associations of these p

42 Two a posteriori methods were used to extract Western and pr

43 n linear time using forward-backward maximum-a-posteriori methods.

44 hough this matrix has more missing data, our a posteriori partitioning strategy reduced the possibili

45 The method follows a maximum a posteriori principle to form a novel network score tha

46 e reconstruction algorithm utilizing maximum-a-posteriori principles and integrating the statistical

47 mized data to determine the critical maximum a posteriori probability (MAP) values for statistical si

48 ation maximization and 3-dimensional maximum a posteriori probability (MAP3D) algorithms.

49 stance to the set of samples chosen from the a posteriori probability distribution of transcription f

50 asone plasma concentrations by using maximum a posteriori probability estimation; we evaluated covari

51 The software is also capable of maximum a posteriori probability image estimation (MAP-SIM), an

52 The idealization is sought to maximize a posteriori probability of the state sequence correspon

53 pper Midwest in 2009 were 2.9 Tg, 61% lower (a posteriori scale factor of 0.39) than our a priori pre

54 A posteriori scale factors for the U.S. anthropogenic CO

55 and, they can be used as a spectrum-adapted, a posteriori score for database search.

56 that best "explains" it, called the maximum a posteriori skeleton.

57 of freedom allowing the parties to convert, a posteriori, the two-mode correlations of the eavesdrop

58 ategories of individuals that were predicted a posteriori to be dispersers (adult males) and philopat

59 We use family information a posteriori to select only the most reliable CNV region

60 ts logistical convenience, the concept of an a posteriori treatment recommends itself to be evaluated

61 though this Edisonian approach is useful for a posteriori understanding of the factors governing asse

62 relative to the use of partitions identified a posteriori using a Bayesian mixture model.

63 nic episodes have been clinically classified a posteriori using preset criteria.

64 A posteriori, we show that the estimated feature field i