# Advances in post-processing methods for multiple sequence alignment

## TL;DR

This review summarizes the development of post-processing methods for improving multiple sequence alignment accuracy over the past 30 years.

## Contribution

The paper offers a systematic overview and future directions for MSA post-processing methods.

## Key findings

- Post-processing methods have shown potential in improving alignment accuracy.
- There is a lack of systematic reviews on MSA post-processing methods.
- The paper outlines potential future research directions in the field.

## Abstract

The reliability of multiple sequence alignment (MSA) results directly determines the credibility of the conclusions drawn from biological research. However, MSA is inherently an NP-hard problem, making it theoretically impossible to guarantee a globally optimal solution. Consequently, in addition to developing more efficient alignment algorithms, improving the quality of initial alignments through post-processing optimization has become an important strategy for enhancing the overall alignment accuracy. Although post-processing methods have shown potential in improving alignment accuracy, currently, there is a lack of systematic reviews and summaries. In this review, we provide a systematic overview of the development and key research ideas of MSA post-processing methods over the past 3 decades and outline potential directions for future research.