Sentence examples for alignment produces from inspiring English sources

Linear alignment produces reliable results but the introduction of nonlinear methods can improve matching by accounting for global brain shape.

In brief, SHERA takes overlapping short reads as input, finds the best alignment, produces a composite read, calculates new quality scores for the overlapping bases, and scores the alignment confidence.

While sequence alignment works best for closely-related homologous proteins, i.e. proteins sharing at least 40% of their amino acid residues, structure alignment produces a significant alignment even between highly diverged homologous proteins [1].

The phylogram (Fig. 3B) obtained from the alignment produces strong bootstrap support for three genus-specific clades, containing three genes for Ae. albopictus and Ae. aegypti, two for Culex quinquefasciatus, and one for each anopheline, An. stephensi, An. funestus, An. gambiae, An. darlingi, An. albimanus, and An.

Nucleotide sequences were aligned according to corresponding aminoacid alignment produced by MUSCLE (Edgar 2004), and frameshift mutations were corrected manually.

Certainly, the alignment produced by the proposed method seems to be good.

The lower scored whole ITS SATé alignment produced the most dissimilar trees, and the corresponding multiple alignment was found to be very suboptimal.

Both the best-scored whole ITS SATé alignment and the 5.8S re-included SATé alignment produced phylogenetic trees with the highest topological similarity to published multi-gene phylogenies.

Initial analysis of the NGS sequence results was conducted using the GSMapper software package, which is optimized for the long read alignment produced by the GS FLX platform.

The resulting tags with at least one BLAST alignment producing a bitscore of 30 or above were assigned as putative mRNA transcripts.

Bayesian analyses using this alignment produced a phylogeny with fairly high support for both the backbone nodes and the internal branches (Fig. 2).