Sentence examples for methods statistical support from inspiring English sources

For both methods, statistical support for the branches was assessed performing 1000 bootstrap replicates.

Although sister relationships between PmKCNAα/β and KCNA10 as well as between PmKCNAδ/ε/ζ and KCNA4 were recovered by both methods, statistical support for these relationships were not high (BP: 11~59; PP: 0.39~0.97).

Application of the method gives statistical support for a more aggressive interpretation of microarray intensity data.

Finally, we supplemented our phylogenetic analyses with probabilistic search methods that provide statistical support for the identification and orthology delineation for protein domains.

Phylogenetic trees on the basis of partial 5′ (339-nt) and 3′ (520-nt) ends of the spike protein gene were elaborated by using parsimony and neighbor-joining methods, which supplied statistical support with bootstrapping >1,000 replicates.

Despite general lack of agreement among partitions and methods of analysis and statistical support for the relationships of the principal pteropodid clades, two groupings seem to be slightly favored.

In cases where agreement between methods was lacking or statistical support was marginal, identification of conserved sequence motifs, inspection of predicted structure and clustering of homologous proteins were applied to obtain function predictions.

Furthermore, and in contrast to the PSMC framework (Li and Durbin 2011) that qualitatively documents changes in population size, our method explicitly assesses the statistical support for a bottleneck model over a null model (see Table S3 for the pros and cons of alternative demographic inference methods).

Consensus assignments based on both approaches together were found to be often more correct than either method individually, even when the statistical support for assignments was low.

ST is an improvement of the classical hierarchical clustering method (HCL) [ 36] implementing statistical support for the nodes of the trees based on resampling the data, in our case by bootstrapping from 100 iterations.

Compared with parsimony based methods that require prior assumptions about statistical support, TERA is distinguished by its ability to estimate a statistical support threshold from its input.