Sentence examples for data transformation step from inspiring English sources
As the first data transformation step for a given double-mutant fitness matrix W (Figure 5), we investigated whether some simple data preprocessing option, such as removing potential location shifts in W before performing its approximation, was able to improve the discrimination power of the data matrix.
Therefore, the performance of the predictive algorithm was not affected by this data transformation step.
We retained 75 principal components of PCA in the preliminary data transformation step, which altogether contained more that 85% of the total genetic variation.
For accurate molecular subtyping, we present an alternative approach to gene centering that incorporates a routine data transformation step prior to subtyping.
To avoid over-fitting, we retained only the 111 first principle components (PCs) from the preliminary data transformation step (indicated to be the optimal number based on the optim.a.score function), representing 46% of the total variation in the data set (analysis including all PCs yielded virtually identical results).
It is believed that the extracted results using nonlinear curve fitting method is more accurate due to the utilization of actual data and the minimization of data transformation steps required in the linear curve fitting [42, 43]. Figure 7 shows the J-E results for the samples annealed in O2, Ar, and FG ambient, which fitted well with FN tunneling model.
In GeneSpring, normalization and data transformation steps for one-colour data were applied as recommended by Agilent Technologies.
The normalization consists of the following three steps: first, data transformation (set measurements less than 300.0 to 300.0); second, per chip (normalize each chip to the 50th percentile of the measurements taken from that chip); and third, per gene (normalize each gene to the median of the measurements for that gene).
The gene expression data and knowledge-based data after the transformation step were analyzed separately by GENN with the following parameters, population sizes of 25,000 per deme, 20 demes (populations), 300 generations, and migration every 15 generations.
Regarding the data transformation and analysis step, there is potential for probabilistic text mining methods.
