Develop direct optimization algorithms for general MSAs

Develop efficient algorithms that directly optimize EDS cardinality and size measures on general multiple sequence alignments containing gaps, rather than treating gaps as ordinary symbols and removing them after segmentation.

Background

The paper gives linear-time algorithms for gapless MSAs and uses the gaps-as-symbols strategy as a practical heuristic for general MSAs. However, the authors state that this approach does not work for arbitrary MSAs and all quality measures, including size. They therefore leave open the development of efficient algorithms that optimize the relevant measures directly on general alignments with gaps.

References

The above approaches will not work for arbitrary MSAs and all quality measures (like size), so it is natural to ask if there are efficient algorithms to directly optimize the measures on general MSAs.

— Pangenome Optimization via Elastic Degenerate Strings  (2609.26542 - Rizzo et al., 22 Sep 2026) in Section Discussion, subsection “Tailored algorithms with gaps.”

Alternatively, there may be slight adjustments to the measures that are amenable to efficient algorithms: in different contexts, the notions of prefix-aware height and segment length (which is different than the string length after the removal of gaps) have been introduced or optimized.

— Pangenome Optimization via Elastic Degenerate Strings  (2609.26542 - Rizzo et al., 22 Sep 2026) in Section Discussion, subsection “Tailored algorithms with gaps.”