Fig. 3 a Algorithmic specification and b the graph of variation of the storage requirement for the signals A, B, C, D, and E. The abscissae are the numbers of assignment instructions executed at run time; the ordinates are the memory locations (or words, whose width in bytes is known) in use.
A cluster of 101 genes up-regulated in the hESC sample [see Additional file 1], was plotted in a centroid graph; the variation across technical replicates was low.
In each graph,the variations of cwnd/ssthresh are represented.
In order to compare in the same graph the variations of the parameters having different units (Intensity, Area Fraction) we calculated for each parameter the "centered and normalized" value using the formula: Xt = (Xt−meanX)/ Xmax−Xmin).
Error bars on graphs represent variation from biological and/or technical replicates.
The graphs illustrate variation in spike amplitude ratio both within and between groups.
Based on an e stimate of the next two years' data on effort and environmental regime, an exploratory prediction is proposed for catches per unit of effort (CPUE), and a graph gives variations in "maximum sustainable yields mSY)" and "optimal fishing efforts (fmax)" according to different environmental regimes.
Upon examining these graphs substantial variation between the cell lines is observed with the most castration resistant cell line, PC3, having the weakest response generally to the various treatments, followed by moderate responses in LNCaP cells, and strong sensitivity to certain growth factors in MDA-PCa-2b cells.
As stated in " De Bruijn graphs and variations in the transcriptome", the weights of the de Bruijn graphs considered here are integer, but not necessarily bounded.
One of the factors possibly contributing to a better performance of BIN and BIN-NO-DEC is the fact that cDBGs, as stated in " De Bruijn graphs and variations in the transcriptome", have bounded degree and are therefore sparse.
