On average, computing the distribution for text length 1000 took 97.4 ms using the compound Poisson approximation and 121.1 ms using the exact method on an Intel Core 2 Duo CPU at 2.66 GHz, running Linux 2.6.24.
On average, computing times per data set ranged from approximately 20 min (genomic BLUP) over 77 min (universal kriging) to 227 min (simple kriging), but no special efforts were made to achieve computational efficiency at this stage.
Additionally, it reduces, on average, the computing time of the exact methods by approximately 99%, and this offering high-quality discrete approximations of the true Pareto-front.
On average while computing arrangements with few degeneracies (on sample molecular models), it is shown that certifying the result incurs a modest factor of two with respect to calculations using a plain double arithmetic.
This filtering step rejected on average 60% (computed on 56 TF families) of misannoted TF sequences, based on the absence of the typical TF INTERPO domain.
By analyzing the alignment rate increase of OPTIMA compared to Gentig, a 1.5 to 2.9 times increase on average, we computed the corresponding cost reduction to be 33 66 %, with an average cost reduction of 54 % for relaxed filtering of data (r) and 49 % for stringent filtering (s).
Using a single core on the Intel Core i7 CPU, on average, it can compute the HSIC between the quantitative phenotype and ~800 SNP pairs per second in R. The GPU runtimes with varying number of SNP pairs are plotted in Figure 2. It is observed that GPU runtime varies linearly with the number of SNP pairs tested.
On average, they rated engineering, computing, and science fields as more likely to fulfill agentic goals than communal ones.
On average, the AA pipeline computed complete annotation of a phage genome in 10 CPU hrs; manual inspection of the gene calls that were flagged as having potential issues required approximately one day per genome.
A pan-cancer ranking of samples based on average levels of methylation computed over our proposed panel of 89 markers corroborates that this set can distinguish CIMP+ from CIMP− samples with very high accuracy.
We expect this average probability to be in, or close to the interval between p(C) and p(d), which were the averages computed on, respectively, the control set and the disease set d during cross-validation.
