Sentence examples for transformation outcome from inspiring English sources

Simple line notations have been useful as chemical structure identifiers and bearers of information necessary for the vast majority of cheminformatics tasks, such as chemical database searching or basic reactive transformation outcome predictions.

This review summarizes recent knowledge and puts forward novel ideas on how dynamics in the epigenetic landscape of myeloid cells shape the development, immune activation and leukemic transformation outcome.

This paper finds that organisational performance is driven by innovation only when mediated through these transformation outcomes.

Transformation outcomes were measured by the acquisition of resistance to kanamycin (Kanr).

A more comprehensive analysis of transformation outcomes has been made in Arabidopsis thaliana, where the number of T-DNA copies integrated at a single site appears to be dependent not only on the identity of the A. tumefaciens strain and the explant, but also on the transformation methodology as well as the origin of replication of the vector providing the T-DNA [ 22].

Calibration refers to the transformation of outcome indicators and causal conditions into membership sets.

Transformation of outcome variable: e.g. log-transformation for skewed continuous positive variables [ 18], or variance-stabilizing transformations (e.g. inverse hyperbolic sine-transformation for non-negative count variables).

1 By this transformation, the outcome becomes dimensionless and the scales become comparable, as the results are expressed in standard deviation units.

2 By this transformation, the outcome becomes dimensionless and the scales are comparable, because the results are expressed in standard deviation units.

Adjusted outcomes were assessed using multi-variable linear regression (percent area stenosis, Gensini score) or logistic regression (collateral formation) with logarithmic transformation of outcome variables as needed to preserve normality.

Pre-processing in the case of 2D gel analysis includes: 1) normalizing intensities to remove effects of differential loading and staining; 2) transformation of outcome variables to normally distributed variables; and 3) imputing values for missing spot intensities.