DCAlign v1.0: Co-evolution models and informed priors are used to align biological sequences

              In columns of multiple sequence alignments of homologous sequences, the conservation and co-evolution signals are characteristics that the novel alignment method DCAlign is able to handle. However, the computationally intensive pre-processing processes needed to align a candidate sequence. In version 1.0, the authors demonstrate how to incorporate an empirical prior across a useful set of variables that mirrors the existence of insertions and deletions in order to significantly reduce the overall computing time.

   Julia is used to implement DCAlign v1.0, which is entirely accessible at https://github.com/infernet-h2020/DCAlign.

Reference:

Muntoni A.P. et. al. (2023) DCAlign v1.0: aligning biological sequences using co-evolution models and informed priors. Bioinformatics 39(9): btad537