Sentence examples for matrices with data from inspiring English sources

In relation to this problem of compatibility between marker-based and pedigree-based relationship matrices, with data from routine evaluations, selection affects the allele frequencies over time, and in principle both observed marker genotypes and observed phenotypes contain information about allele frequencies in the base population.

We compare this matrix with data from the 2001 and 1991 census surveys.

The interaction pattern can be described as a presence absence matrix denoting the observed and unobserved interactions (as shown here) or a quantitative matrix with data on interaction strength for each observed pairwise interaction.

Furthermore, in terms of the abnormal data, the authors in [107] also investigated to use the statistical learning theory of sparse matrix with data cleansing for the robust spectrum sensing.

Furthermore, we constructed a principal coordinate analysis (PCA; [31]) graph in GenAlEx to visualize a covariance matrix with data standardization derived from the pairwise FST values to more effectively view the patterns of genetic distance among populations.

Analyses were performed using the covariance matrix with data standardization of genetic distance using GenAlEx.

Principal co-ordinate analysis was based on the distance matrix, with data standardization provided by the GenAlex package.

Figure 3 shows a heat map of the data matrix with data organized based on gene tree and condition tree clusters.

For our study, we compiled several sociomatrices taken longitudinally at key points in the class, as well as one matrix with data of interest about our students.

The analysis were based on the pairwise genetic distance (i.e. number of loci with differing alleles) matrix, with data standardization (i.e. division by the square root of n-1).

The same genetic divergence among samples was observed using the Principal Coordinate Analysis (PCoA) approach based on a genetic distance matrix with data standardization, where the first axes explained 38.51% and 53.10% of variance and the second axes 21.29% and 23.56%, for SSR and SNP marker loci respectively (data not shown).