The phrase "alignment of contacts" is correct and usable in written English.
It can be used in contexts where you are discussing the arrangement or coordination of various contacts, such as in networking or communication.
Example: "The alignment of contacts within the organization is crucial for effective collaboration and information sharing."
Alternatives: "coordination of contacts" or "arrangement of contacts".
For example, Contact Map Overlap (CMO) problem [41] measures protein structural similarity based on a graph alignment of contact maps; a contact map is simply the adjacency matrix of a RIG, while contact map similarity is the maximum number of common contacts that can be efficiently approximately computed.
Our algorithm is optimal for pairwise alignment of contact maps and near-optimal in practice for multiple alignment, while having polynomial-time complexity.
Once all values of M are computed using (2), the optimal alignment of contact maps is determined by backtracking through the scoring matrix as in standard dynamic programming.
For each family, we will use the multiple alignment of contact maps corresponding to each PPI complex within the family and generate aligned core regions within each sequence pair.
In the case of multiple alignment of contact maps, although the neighbor-joining method is not optimal, it has been shown in practice to perform nearly as well as an optimal, exhaustive search for multiple sequence alignment (Gascuel and Steel, 2006).
Multiple alignment of contact maps is accomplished using the same neighbor-joining algorithm as in CLUSTALW (Higgins and Sharp, 1988), but with similarity of contact maps as a distance metric: (5) The final step of our algorithm identifies core regions within each of the interface sequences.
Instead, given our null model, expectation scores can be defined based on the alignment of the query contact map against a random contact map generated according to our model.
Movements within the scoring matrix correspond to the following alignment actions: An optimal alignment it A of contact maps is a mapping A i, j)=(a(i), b j)) of the pair of (i, j) indices from a complex C onto the (k, m) pair in a complex D where (k, m)=(a(i), b j)).
We conclude that the corrected alignment was more informative than the initial alignment for contact prediction.
We confirmed a precise agreement between the denser regions of IRs in the alignment of ISTs and the contact regions in the 3D structure data (Figure 2A, blue).
