Suppose { ( x i, f i ), i = 1, 2, …, n } is a given monotonically increasing data set.
Clearly, these conclusions rely on the sampling, and could be changed with increasing data set.
Further, with increasing data set size, phred cutoffs limit erroneous sequences to a smaller sequence pool.
The mutations identified in these 84 families add to the increasing data set of the IPCRR of detailed clinical information and corresponding molecular data of individuals with PC.
Concurrently, emerging methods provide new virus host linkage capabilities, but do not scale well with increasing data set size and complexity (e.g., Andersson and Banfield, 2008; Tadmor et al., 2011; Allers et al., 2013a; Deng et al., 2014).
In contrast to previous analyses of mitochondrial genomes the increased data set recovered the classical echinoderm phylogeny of Eleutherozoa and Echinozoa in Maximum Likelihood and Bayesian analyses using hemichordate out-group representatives.
This is in contrast to fold changes in which increased data set variance can randomly produce more extreme fold-changes.
Probably the most challenging area currently, is the downstream analysis of data, mainly because of the increased data set size.
Moreover, time-resolved technique will be combined with structured light tomographic method in order to increase data set information and, e.g. to discriminate scattering and absorption contribution.
Still, increased data set size can pose a problem for congruence tests that involve pairwise comparison (Planet and Sarkar 2005; Leigh et al. 2008).
Current trends in optical imaging focus on the construction imagers that yield an increased data-set of optical measurements per examination, so that higher resolution and quantification accuracy is achieved.
