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Genomic relationship matrices weighted by marker realized variance yielded more accurate and less biased predictions for traits regulated by few QTL.
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matrix weighted by edge degrees DRA0451 ESpm11x Spectral moment 11 from edge adj.
matrix weighted by resonance integrals GGI8 topological charge index of order 8 nCconj number of non-aromatic conjugated C sp2) O-058 = O (atom-centred fragments).
Thus, both average effective distance (d mn ) and average shortest path tree (that is the shortest path among many effective distances) responsible of outbreak spreading (D mn ) depend only on the static mobility matrix weighted by the food fluxes.
matrix weighted by dipole moments DRA0551 GGI2 Topological charge index of order 2 DRA0565 JGI6 Mean topological charge index of order6 DRA0670 nRNNOx Number of N-nitroso groups (aliphatic) DRA0695 Numberumber of phosphates/thiophosphates DRA0791 N-067 Al2-NH DRA0802 N-078 Ar-N = X/X-N = X.
With topological descriptors, QSAR were based on χpc for 58 PCB (Brunner et al., 1990), and on the highest eigenvalue number 7 of Burden matrix, weighted by Sanderson electronegativities (BEHe7) for 209 PBDE and HBB (Papa et al., 2009).
Within the framework of single step procedure (Misztal et al. 2009; Aguilar et al. 2010), an "iterated-GBLUP" algorithm was proposed for genome-wide association study (GWAS) purpose by building a trait-specific G matrix weighted by derived marker effects within the iteration procedure (Wang et al. 2014).
Among the 974 genes belonging to the ξ matrix, we finally retained, for the final gene signature, in a ξ′ matrix, 322 genes as function of a threshold (P=0.001) on the frequencies of relevance, which is defined as the frequency at which a given gene and a given tumor are found together in a selected training matrix, weighted by the number of training tumors well classified by this training matrix.
Distance matrices were weighted by the inverse of their variances to account for differences in reliability.
The normalized total criteria relation matrix was weighted by the normalized total dimensions matrix to obtain an originally weighted super-matrix by Eq. (11), and the matrix was then transposed to get the weighted super-matrix using Eq. (12).
The former is an extension of the 'negative pick matrix' in which the entries of the pick matrix are weighted by the magnitude of the sentiment measures.
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