Sentence examples for stable trees from inspiring English sources

The price paid is that stable trees that cross-validate well usually consist of no more than a few terminal nodes and are thus not very discriminating [ 24].

In particular, we obtain more stable trees due to the exclusion of phylogenetically incompatible sites that most likely represent strongly randomized characters.

The CV method could use the information from all coding proteins so that it may still construct stable trees even dashing with a few horizontal transferred genes.

Likewise, no stable trees could be obtained from the subsection of the alignment limited to the conserved motifs, e.g. absolutely reliable regions, perhaps due to the insufficient number of compared positions (data not shown).

Somewhat surprisingly, the trees based on all k-mers also appear to be unstable with increasing K. On the other hand, the distance based on maximal words seems to produce consistent and stable trees.

The analysis of several published data sets shows that removal of randomized sites consistently leads to more stable trees, irrespective of the method used for phylogeny reconstruction (neighbor joining, maximum parsimony, or maximum likelihood).

This showed that a stable tree topology requires seven or more genes (data not shown).

The most stable tree was obtained from all SNP positions, including non-synonymous, synonymous, non-coding and intergenic loci.

These receptor sequences do not show stable tree topology and group with different subfamilies when using different phylogenetic algorithms.

Are trees for different word lengths converging on a stable tree or is the tree based on each n-letter word different?

But it allowed us to avoid alignments that are obviously suboptimal, and we could show that these class-3 alignments produce stable tree topologies.