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The data configuration is coded by the rules presented in the section A simplified multilocus model for haplotype structure as shown in Table 6.
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A significantly greater fit of the tree to the original data configuration is interpreted as evidence for the presence of significant phylogenetic signal, which suggests that the character (e.g., biomechanical parameter) in question has not evolved rapidly [ 36].
In addition, robust numerical algorithms that are guaranteed to work for all but known extreme data configurations are essential.
Data loss occurs in several ways and depends on the data configuration: (i) if proteins are not assigned to a family in a particular family approach; (ii) if transcripts encode non-protein coding genes and a protein family approach is selected; (iii) if gene sequences are not covered by a (microarray) platform; (iv) if significance criteria, as defined by the user, are not satisfied.
We are in the data configuration proposed in Equations 24 and 25 which is recalled in the following equations: X = α S + C + N (37) X k = C k + N k k ∈ [ 1, K ], (38).
For larger files, on the order of GBs for raw data, such configuration is not suitable, since this requires loading the full XML tree into memory.
In addition, data rate configuration is performed at the sender.
The diagram of the network configuration is included in supplementary data (Additional file 1: Figure S4).
The data from each configuration were collected for five seconds.
Accurate pixel-wise comparison between simulated and acquired RS data, for any configuration is another important application of this approach.
Automatically, a data configuration proposal is generated and the devices available within range are identified.
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