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We have also followed this approach, and employed a variant of the Hough transformation [25] to determine the center and radius of the circle.
An algorithm written in Perl was produced to implement this approach and employed to independently shuffle the concatenations of regulatory, nonfunctional and coding sequences.
Most of the studies carried out thus far have adopted a label free quantitation approach and employed low resolution mass spectrometers to identify the proteins differentially expressed between RA and OA.
To identify which codon sites were under positive or purifying selection we used a Bayesian inference approach and employed the Selecton server ([ 49], [ 50]; http://selecton.tau.ac.il/) to run model M8 [ 51] and when positive selection was detected to run the model M8a versus model M8 as a statistical test of significant positive selection.
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The proposed method is a circuit based branch-oriented approach and employs a current summation algorithm for loss allocation.
The method is based on the moving mesh partial differential equation approach and employs its newly developed implementation.
This computational hemoacoustic method is based on the immersed boundary approach and employs high-order finite difference methods to resolve wave propagation and scattering accurately.
Results are obtained by using a modified version of Rayleigh's approach and employing two different types of co-ordinate functions.
The model is based on an equivalent circuit approach and employs robust, globally continuous equations to describe the non-linear circuit elements.
Swallowing accelerometry is one such approach and employs an accelerometer as a sensor during cervical auscultation.
In line with previous works (see for example [2]), we here pursue the latter approach and employ standard non-parametric tests to moving time windows.
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