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We demonstrate significant increase in the alignment accuracy of several well-known distance-based alignment methods, obtained by utilizing the superpositions that rigorously optimize a very simple and intuitive alignment metric, defined as the largest number of residues from the input proteins that can be fit under a predefined distance cutoff.

To illustrate how the transitive alignment metric works, consider the human genome MIR element at hg18 chr10:364, 241-364,409.

As evaluated by Mahony et al. [ 11], the PCC metric combined with the SW ungapped alignment algorithm (PCC/SWU), and the SSD metric combined with SW alignment (SSD/SW) with gap extension equal to 0.5 and gap open equal to 1, are the best two metric and alignment settings on Dataset-1 among the five column similarity metrics associated with their all possible alignment settings.

The methods in STAMP can be selected by specifying the column comparison metric and alignment method [7].

In contrast, global biodiversity targets such as those agreed to in the Convention on Biological Diversity (CBD) (6) tend to be less specific, and the alignment of metric, indicator, and target can be poor.

Most of current motif comparison methods are divided into two parts: a column similarity metric for comparing two columns which come from the PFMs (or the PSSMs) of two motifs respectively, and a pairwise alignment algorithm for the two motifs using the column similarity metric and a penalty function for gaps [ 11].

We refer to the final metrics in the two cases as optimized metric and average metric.

For global alignment, we use a graph-based approach making use of the same error metric and iteratively refine the complete vehicle trajectory.

Initial matrices are computed by maximizing the centered-kernel alignment (CKA) metric, measuring the affinity between projected samples and labels.

The CAI (Collagen Alignment Indenx) metric is a quantitation of these values and lets us put any given tissue within a range of tissue development over time.

We additionally classified them using the alignment comparison metric (overlap score) as implemented in mumsa version 1.0, 48 which also infers UPGMA dendrograms from these similarity values.

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