Contrasting statistical patterns in melodic and molecular evolution reveal distinctive constraints in a culturally evolving system
arXiv:2607.12673
The paper introduces a rhythm-aware sequence alignment method to analyze thousands of Irish folk melodies, revealing evolutionary patterns that differ from those in protein sequences and highlighting cultural constraints on music transmission.
Abstract
Evolved sequences can be used to infer the rules of evolution. Orally transmitted folk melodies are evolved sequences whose similarity to protein sequences (one-dimensional, drawn from a limited alphabet) invites application of bioinformatics methods to study cultural evolution. A major obstacle is that melodies encode rhythm, which breaks some assumptions of standard sequence-alignment algorithms. We develop a rhythm-aware alignment method and apply it to \num{40000} Irish dance tune variants, enabling the first large-scale automated melodic alignment. Four canonical bioinformatics analyses -- mutability, substitution matrices, positional conservation, and covariance -- reveal patterns distinct from those of molecular evolution, revealing the forces that shape each domain: biochemical and biophysical constraints for proteins; memory, motor, and social biases for melodies. Together the results show that bioinformatics provides a powerful framework -- conceptual as much as algorithmic -- for studying cultural evolution. Although the cultural transmission of music has been discussed for centuries, here we show how to analyze it at large scale.
13 pages, 3 figures, 12 extra pages of supplementary information