Mapping Equivalence for Symbolic Sequences: Theory and Applications

TL;DR

This paper introduces a theoretical framework to analyze when different numerical mappings of symbolic sequences are equivalent, ensuring that results in symbolic signal processing reflect inherent data properties rather than artifacts of the mapping.

Contribution

It develops a novel algebraic and correlation-based framework for assessing the equivalence of symbolic sequence mappings, with theoretical conditions and practical DNA analysis applications.

Findings

Established conditions for mapping consistency

Introduced an algebraic framework for equivalence

Applied to DNA sequence analysis

Abstract

Processing of symbolic sequences represented by mapping of symbolic data into numerical signals is commonly used in various applications. It is a particularly popular approach in genomic and proteomic sequence analysis. Numerous mappings of symbolic sequences have been proposed for various applications. It is unclear however whether the processing of symbolic data provides an artifact of the numerical mapping or is an inherent property of the symbolic data. This issue has been long ignored in the engineering and scientific literature. It is possible that many of the results obtained in symbolic signal processing could be a byproduct of the mapping and might not shed any light on the underlying properties embedded in the data. Moreover, in many applications, conflicting conclusions may arise due to the choice of the mapping used for numerical representation of symbolic data. In this paper, we present a novel framework for the analysis of the equivalence of the mappings used for numerical representation of symbolic data. We present strong and weak equivalence properties and rely on signal correlation to characterize equivalent mappings. We derive theoretical results which establish conditions for consistency among numerical mappings of symbolic data. Furthermore, we introduce an abstract mapping model for symbolic sequences and extend the notion of equivalence to an algebraic framework. Finally, we illustrate our theoretical results by application to DNA sequence analysis.