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Our data selection steps [for example, steps III, IX and XV] guarantee standardized levels of the density of the data set and of sequence overlap between included species.
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In special, select cases where the density function of the data set forms a perfectly symmetrical curve with one mode (for example, the Gaussian or "Bell-Shaped" Curve), the mode, mean, and median will all be the same value.
In density-based methods, communities are defined as areas of higher density than the remainder of the data set.
The difference in mean helix/strand density between the highest and lowest thirds of the data set with respect to the evolvability index is also significant.
Another reason for the generally harmful effect of edge density on performance could be the correlation strength of the data set.
Data for the distribution and density of cis-regulatory elements are not provided for mouse conserved events due to the extremely reduced size of the data set.
In order to assess the performance of existing applications on high-density microarray data sets and compare their results to CGHScan it was often necessary to use only a portion of the data set, otherwise many programs would not be able to accommodate the data or complete the analysis.
Projections of the data set onto these eigenfunctions reduces the data set to a set of data coefficients.
The contact densities of the proteins in the data set have a mean value of 5.1 and a standard deviation of 1.0, the helix/strand densities have a mean of 0.082, and a standard deviation of 0.023, and the evolvability indices have a mean of −0.0095 and a standard deviation of 0.066.
To inspect translation on a genome-wide scale, ribosome density values of each gene expressed in the data set were organized in the same order as the transcriptome.
For density modification with ShelxE, the high-resolution data set was merged with the data set used for phasing.
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