A time warping approach to multiple sequence alignment

TL;DR

This paper introduces a novel multiple sequence alignment method based on dynamic time warping and curve synchronization, constructing a median path from pairwise alignments, with promising initial results on synthetic and benchmark data.

Contribution

It presents a new approach to MSA using dynamic time warping and median path construction, integrating functional data analysis techniques.

Findings

Successful synthetic experiment demonstrating feasibility

Competitive results on benchmark dataset

Potential for integration into existing MSA tools

Abstract

We propose an approach for multiple sequence alignment (MSA) derived from the dynamic time warping viewpoint and recent techniques of curve synchronization developed in the context of functional data analysis. Starting from pairwise alignments of all the sequences (viewed as paths in a certain space), we construct a median path that represents the MSA we are looking for. We establish a proof of concept that our method could be an interesting ingredient to include into refined MSA techniques. We present a simple synthetic experiment as well as the study of a benchmark dataset, together with comparisons with 2 widely used MSA softwares.