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Spatial coverage of the entire dataset for six different time periods, accompanied by the frequency of data points per city for each period, is pictured in panels a-f of Fig. 5. Panel g shows population-weighted global mean centers (GMCs) for each of the six time periods.

Despite Chandler's accomplishment in creating the dataset, the resulting population data are temporally and spatially sparse as illustrated in Figs 5 and 6. Figure 5 provides a snapshot spatial view of all data points across the entire dataset for given time periods and highlights the number of population values for each city, while Fig. 6 illuminates the dataset's temporal sparseness.

Figure 3 shows the position MSE for the standard and the projective particle filters for 80 trajectories in Video_008 sequence; the average MSEs are 1.10 and 0.58, respectively.

Yet, in the most recent release such structure holds up to 16MB of data, much smaller than the required for indexing the entire dataset for Rating with our strategy.

We randomly divided the entire dataset into two disjoint subsets with the same size (i.e., 31,923 subjects), that is, a training set and testing set, where the training set contains 15,596 males and 16,327 females, whereas the testing set contains 15,497 males and 16,426 females2, with a similar distribution as that of the entire dataset for both subsets.

For this I will utilize our Informatics for Integrating Biology & the Bedside (I2B2) installation (note that this is not on our entire dataset for INPC), a de-identified count-based system, to demonstrate on real patient data how this shakes out.

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The 3000-sample dataset for the three-way ANOVA was prepared in two ways: (i) it was built from parts which contain 125 samples individually (same as for the two-way ANOVA) for each of the data pretreatment methods (125 × 8 × 3), and (ii) it was built from the entire datasets for each data pretreatment method (1000 × 3).

The entire datasets (for miRNA and mRNA) described here are available from the Gene Expression Omnibus (GEO, ) through series accession number GSE17060.

Conservation of amino acids in a column, for the entire dataset and for each family individually, was calculated using the method described by Livingstone et al [28].

From the resulting consensus sequences, a genomic 'pseudo-reference' FASTA file was generated for the entire dataset, suitable for anchoring contig alignments across individuals.

Transcripts were scrutinised by the core team (VB, LH, LHS, JN) to get a feel for the entire dataset and for significant emerging themes.

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