Sentence examples for between sequences were then from inspiring English sources

Distances between sequences were then calculated as d = (100-%ID /100 and collected into matrices.

Sequences were then aligned with ClustalX 1.81 [32].

Fragmentary sequences were then deleted.

Matching sequences were then removed.

The selected sequences were then chopped into 40 bp segments and screened for GC content of between 40% and 60%.

A Neighbor-joining phenetic tree based on distance matrix between nucleotidic sequences was then reconstructed for each HGG and used as starting tree for Bayesian inference and Markov Chain Monte Carlo simulations (B/MCMC) (only possible with HGG of 4 sequences and more; the Neighbor-joining tree reconstructed with PAUP* was used for HGG of 3 sequences).

The distance between the homologous flanking sequences was then measured in B. neohumeralis or B. jarvisi (where the flanking sequences were on the same contig).

The ASD between the original and quantized LSF vector sequences is then calculated.

The sequence was then cloned between the BamHI and XhoI sites of the pAL-KS vector.

The relative ranking of each sequence was then compared between PFMs derived from arrays with and without CREB1.

The fem-3 sequence was then subcloned between two opposing T7 promoters in plasmid L4440 (Timmons and Fire, 1998), and dsRNA was synthesized in vitro with T7 polymerase using standard protocols.