Computing distribution of scale independent motifs in biological sequences

Joana S. Almeida, Susana Vinga

Research output: Contribution to journalArticle

11 Citations (Scopus)
3 Downloads (Pure)

Abstract

The use of Chaos Game Representation (CGR) or its generalization, Universal Sequence Maps (USM), to describe the distribution of biological sequences has been found objectionable because of the fractal structure of that coordinate system. Consequently, the investigation of distribution of symbolic motifs at multiple scales is hampered by an inexact association between distance and sequence dissimilarity. A solution to this problem could unleash the use of iterative maps as phase-state representation of sequences where its statistical properties can be conveniently investigated. In this study a family of kernel density functions is described that accommodates the fractal nature of iterative function representations of symbolic sequences and, consequently, enables the exact investigation of sequence motifs of arbitrary lengths in that scale-independent representation. Furthermore, the proposed kernel density includes both Markovian succession and currently used alignment-free sequence dissimilarity metrics as special solutions. Therefore, the fractal kernel described is in fact a generalization that provides a common framework for a diverse suite of sequence analysis techniques.
Original languageEnglish
Pages (from-to)18-29
Number of pages11
JournalAlgorithms For Molecular Biology
Volume1
Issue numberNA
DOIs
Publication statusPublished - 18 Oct 2006

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