Therefore, a normalization of the length of the sequences must be applied.
The length of the sequences is a parameter of each simulation.
There is also a variation in results with the length of the sequences.
A comparison with other algorithms is included, considering the amount of calculations as a function of the length of the sequences.
Figure 1 An example of a table based on LCSS length of the sequences X = 〈 B, D, C, A, B 〉 and Y = 〈 A, B, C, B, A, B 〉. Here, we show the definition of similarity between human motion features.
The average length of the sequences was 253 bases.
The length of the sequences had less effect on alignment quality, although longer sequences tended to be less well aligned.
The length of the sequences, the number of amino acids and the E-values obtained are summarized in Table 1.
In two of the COLIGOs we minimized the length of the sequences flanking the stem-loops to 4 nt (COLIGO 19a) and 6 nt (COLIGO 122) per repeat.
It also takes account of stochastic noise caused by the finite length of the sequences used to derive the branch lengths using a penalized-likelihood approach.
This low bootstrap value was probably caused by the short length of the sequences (79 residues) and their high identities (>65%), rather than refuting the split of subgroups B1 and B2.
