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A SVM is a machine learning technique that does not minimize an approximation error considering a dataset, but maximizes the distance between the clusters that are to be classified.
Very good separation can be observed between the clusters that are associated with HNC and healthy states.
By this we mean the sum where for each agglomeration step we take the distance between the clusters that are merged.
For any two clusters c i and c j, their similarity is defined as the C2S score value averaged over all protein pairs between the clusters, that is: (8) For any two singleton clusters c i ={ x} and c j ={ y}, it is evident that sim(c i, c j )= C2 S x, y).
It has been suggested that they are reduced but not apparent in spectra due to spin-coupling between the clusters, that the signals are so fast relaxing that they are too broad to be distinguished, or that they exhibit higher spin states so are not observed in the g ∼ 2 region.
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Interactions between the cluster that exhibits signal N3 and the flavosemiquinone radical, and the cluster that exhibits signal N2 and the ubisemiquinone radical, showed that N3 is from the [4Fe 4S] cluster in the 51 kDa subunit, 4Fe[51], and N2 is from the [4Fe 4S] cluster in the PSST subunit, 4Fe[PS].
It has superior discriminative power compared to spa-typing, which was not specific enough to distinguish between patient A (Table 1) and the cluster that was found.
The height of the link (' U') represents the distance between the two clusters that contain those objects, i.e. the shorter the U the more similar the variables are to each other.
A robust SNP genotyping assay is characterized by large distances between the three clusters that define the genotypes and small distances between the data points within each cluster.
We observe a significant overlap between the expression clusters that are enriched in the dauers of both the species (Fisher's exact test p-value = 0.0185), indicating a conserved signature of gene expression.
Despite these limitations, this study confirmed that the QOL of older adults differed between the three clusters that were formed, with a good QOL being strongly associated with good self-rated health, the absence of depressive symptoms, and family satisfaction.
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Justyna Jupowicz-Kozak
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