Summary details of the HA and NA sequences from each subtype are given in Tables 1 and 2. A distance matrix for every dataset was calculated using Kimura's two-parameter model [40].
The Top-10 Lists from every dataset are passed onto Evidence merger, which searches for the most frequently appeared interaction form in the Top-10 Lists of a target gene.
She closed by reminding the audience that "every missing dataset is benefiting someone by not existing," but that examining who benefits, and therefore "who counts," is a goal we as a community can contribute to in our research, our classrooms and our daily lives.
In contrast to the normally applied procedure in which every subject's dataset is fitted with the same design matrix, we used a different design matrix for each subject, based on the subject's actual data ('seed' time courses from the same ROIs) so that the final map reflects regions whose activity is correlated to the activity in the same 'seed' location across subjects.
Every ChIP-Seq dataset is a mixture of directly bound segments and regions that may reflect alternative influences.
We consider every point in dataset is equiprobable; then P(H) = ∑ P x), x in H, where P x) = 1/ n, n is the number of the points in dataset.
An attractive aspect of our approach, which does not use a preselected list of transformations, is that the resulting pair list is comprehensive in the data set used; that is, every transformation in the dataset is considered in the analysis.
In a logarithmic transformation, every value in the dataset is replaced by its logarithm.
For now, the boundary of every emotion in ES dataset is not clear (which is already shown in Figure 11(b)), so it does not meet the condition of closed set, and the result is worse than FM.
An LAD model is simply a collection of positive and negative patterns of good characteristics, with the property that every observation in the dataset is covered by at least one of the patterns.
This means, by definition, no pair of reference shapes has a similarity above 0.75, after diversity selection, and that every conformer in the entire dataset is associated with at least one reference shape with a shape Tanimoto similarity above 0.75.
