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However, in contrast to successive weighting schemes it is not intended to select characters and weights that maximize congruence on a most parsimonious tree, but we select characters that maximize the probability that a support consists of homologous nucleotide patterns in a topology-independent exploration of the alignment.
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Together, these advances allow further exploration of the embedded alignment data space within sufficiently large data sets to eventually induce relevant statistical inferences.
However, our cross sectional design precludes further exploration of the temporal alignment of chronic whiplash and symptoms of anxiety/depression.
Exploration of the data for alignment with normality showed that the pretest and posttest data sets did not display any significant skew or kurtosis (peakedness).
As previously suggested, our results underscore the importance for careful exploration of the sensitivity to the effects of alignment methods for data comprising widely divergent sequences.
It is possible to detect errors introduced in the modelling procedure such as incorrect alignments, which would facilitate the visual exploration of alternative alignments, e.g. as suggested previously in (Barbato et al., 2012).
We now report the further molecular alignment-guided exploration of the chemotype to discover potent and selective PAT analogues.
Possible application of the alignment and assembly free approach requires further exploration for other types of sequencing data, such as RAD-seq and metagenomic data especially for organisms without a reference.
Further exploration of alignment parameters was therefore not necessary.
Multiple sequence alignments (MSAs) were generated using both distance and evolutionary aware methods [ 38, 39] ensuring a comprehensive exploration of alignment space.
Signal averaging is used to optimize the image of the alignment marks for maximum alignment accuracy.
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