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(2018) Computational models of rhythm and meter, Dordrecht, Springer.
In this chapter, I introduce a new device for analyzing musical rhythms and for music composition in general: The Burrows–Wheeler Transform (BWT). It has many applications in the area of bioinformatics. It is used in the research of genomes, for the detection of sequences within the genome, and for the detection of mutations and genetical diseases. In bioinformatics, a genome is represented as a string of the nucleobases that build the structure of DNA. For example, the string ACGT represents the four bases found in DNA: Adenine, cytosine, guanine, and thymine. One can regard the genome as one very long word over the alphabet ({A,C,G,T}). In the case of the human genome, it is a word with over 3 billion letters. Because the complete genome information uses a large amount of computer memory, efficient algorithms, such as the BWT, have been developed in order to keep the genome data compressed, whilst, at the same time, performing exact and inexact pattern-matching. It is a very efficient method when searching for mutations, for example.
Publication details
DOI: 10.1007/978-3-319-76285-2_5
Full citation:
Boenn, G. (2018). The use of the Burrows–Wheeler transform for analysis and composition, in Computational models of rhythm and meter, Dordrecht, Springer, pp. 57-63.
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