An efficient Z-score algorithm for assessing sequence alignments.
We describe an alternative method for scoring of the pairwise alignment of two biological sequences. Designed to overcome the bias due to the composition of the alignment, it measures the distance (in standard deviations) between the given alignment and the mean value of all other alignments that can be obtained by a permutation of either sequence. We demonstrate that the standard deviation can be calculated efficiently. By concentrating upon the ungapped case, the mean and standard deviation...[Show more]
|Collections||ANU Research Publications|
|Source:||Journal of Computational Biology|