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random walkers from each boundary node until a convergence criterion is satisfied based on the number of visits to the nodes in the network.
For given thresholds, the algorithm first computes the optimal discrete inputs for each boundary section to obtain optimal trajectories from each boundary section to the target by a dynamic programming approach.
The second input is w a l k n u m, which is the number of random walkers that are started from each boundary node before convergence is tested.
To avoid picking meaningless outliers, we took the read with the highest read count from each boundary region.
Regions of interest encompassing +/+ and +/- boundaries were analysed to provide the mean fluorescence intensity, and cell centre background was subtracted from each boundary value.
Boundaries were defined as co-localized if the sequences 2.5 kb up- and down-stream from each boundary overlap by at least 1bp.
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Drawing four straight lines from the center to each boundary of the detection window would hit four pixels, as shown in Figure 2a.
On the other hand, if one uses spectral methods, then n φ = (Λ + 2) K − 2. Here, Λ is the number of polynomials per population and the term Λ + 2 comes from the fact that each boundary component, except the ancestral and derived vertices of the K-cube, contributes its own polynomial expansion (Lukic et al. 2011).
In this experiment, 1/16 pixels from each image boundary were cut off.
We calculated the boundary curvature at each boundary point by fitting a circle to that boundary point and the two points 25 boundary points away from it.
Actually, the least core method shrinks the core space simultaneously from each side of boundary until a single point (imputation) is achieved.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com