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For each flowgram corrected by the baseline method, we converted the aligned-to part of the reference genome to a flowgram and noted the flow positions that had a mismatch.
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Before applying the numerical method, we convert the governing DEs into a system of first-order ordinary differential equations (ODEs).
To use the NU method we convert the numerator of the potential term to a second-order polynomial.
Based on the undetermined fuzzy coefficients method, we convert a second-order linear differential equation to the crisp system of linear equations.
In particular, we transform fourth-order impulsive problem (1.1) into a second-order differential integral equation BVP (2.10), and by using the shooting method, we convert BVP (2.10) into a corresponding IVP (initial value problem).
Using previously published methods, we converted the coefficients for the independent predictors into a simplified risk score system (11).
To apply the linear modeling methods, we converted individual genomic features to fit the Gaussian distributions using rank ordered z-statistics (R statistics package).
For each method, we first convert the waveforms of individual stations into a metric function and stack them into a network representative trace.
Using this novel method, we can convert a Boolean (control) network into a linear (bilinear) form.
In addition, in the proposed beamforming method, we efficiently convert the objective SR problem into a convex and low-computation-cost one, i.e., (text {max}~R_{text {sum}}longrightarrow text {min}~R^_{B}).
According to the method of Rousset (1997), we converted pairwise G′′st values into G′′st/(1 − G′′st) for each pair of sampling sites.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com