Sentence examples for alignment we estimated from inspiring English sources

After T-Coffee alignment, we estimated maximum-likelihood gene trees for the alignments with PhyML (Guindon and Gascuel 2003).

For each alignment, we estimated Z T (the statistical significance of T region alignment) by the Monte Carlo method (similar to Section 2.2).

On the basis of the multiple sequence alignment, we estimated the rate of evolution for each CP sequence in order to infer the selective constraints.

For each pairwise human and mouse alignment, we estimated the number of non-synonymous substitutions per non-synonymous site (dN), the number of synonymous substitutions per synonymous site (dS), and the dN/dS ratio.

These we aligned and from the alignments we estimated evolutionary rates.

For each of these three alignments, we estimated a phylogeny using the following procedure.

From these pairwise alignments, we estimated sequence divergence, correcting with the Jukes Cantor model of nucleotide substitution.

From these refined pairwise alignments, we estimated sequence divergence, correcting with the Jukes-Cantor model of nucleotide substitution.

With the alignments we estimated coverage and protein percent identity of the top scoring coding regions per vertebrate group relative to the human sequences.

For two-species alignments, we estimated divergence in the different sequence categories (0-fold and 4-fold degenerate sites, ARs, and introns) for each gene separately and then obtained the genome-wide mean based on these estimates.

From these alignments, we estimated the number of nonsynonymous substitutions per nonsynonymous site (K a) for each of the three branches in figure 2 A by maximum likelihood, using our previously described software (Conant and Wagner 2003).