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Analysis of genomic sequences by Chaos Game Representation
Author(s) -
Jonas S. Almeida,
João André Carriço,
António Maretzek,
Peter A. Noble,
Madilyn Fletcher
Publication year - 2001
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/17.5.429
Subject(s) - generalization , sequence (biology) , markov chain , mathematics , hidden markov model , integer (computer science) , representation (politics) , algorithm , computer science , genetics , artificial intelligence , biology , statistics , mathematical analysis , politics , political science , law , programming language
Chaos Game Representation (CGR) is an iterative mapping technique that processes sequences of units, such as nucleotides in a DNA sequence or amino acids in a protein, in order to find the coordinates for their position in a continuous space. This distribution of positions has two properties: it is unique, and the source sequence can be recovered from the coordinates such that distance between positions measures similarity between the corresponding sequences. The possibility of using the latter property to identify succession schemes have been entirely overlooked in previous studies which raises the possibility that CGR may be upgraded from a mere representation technique to a sequence modeling tool.

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