Sentence examples for sample based method from inspiring English sources

A reference sample based method is suggested for studies that would end up comparing gene signal data from a combination of low and standard RNA templates; no such referencing appears to be necessary when comparing fold-changes of gene expression between standard and low template reactions.

Sample based methods take the Monte Carlo approach of using the observed samples directly as an approximation of their generating distribution, instead of fitting them to a parametric distribution.

For large data sets, a sampling based method called CLARA can be used where after sampling the clustering methodology PAM has been applied to detect the best "medoid".

SRSM is one of the ideal conventional sampling based method for uncertainty analysis and this is accomplished by approximating both inputs and outputs of the uncertain system through stochastic series of well-behaved standard random variable (srv).

To judge whether τ i estimates are problematic, one may develop a sampling based method (see Supplementary Material S2).

In Sec. 3, we describe the importance sampling based method that we developed to speed up the calculation of the Class I diffuse reflectance using Monte Carlo simulations.

We proposed and developed an integrated approach to identify gene regulatory networks, which consists of a novel clustering method (namely motif-guided affinity propagation clustering (mAPC)) and a sampling based method (called Gibbs sampler based on outlier sum statistic (GibbsOS)).

In Sec. 4, we also validate our importance sampling method by comparing it against previous Monte Carlo simulations and we demonstrate the significant computational advantage of our importance sampling based method.

In this paper, we have proposed a new method consisting of a clustering method (i.e., mAPC) and a sampling based method (i.e., GibbsOS) to tackle the problem of regulatory network identification.

We developed an importance sampling based method that significantly speeds up the calculation of the diffusive reflectance due to ballistic and to quasi-ballistic components of photons scattered in turbid media: Class I diffusive reflectance.

During the last decade, sampling based methods for motion and path planning have gained more interest.