Title
Analysis of genomic sequences by Chaos Game Representation.
Abstract
Motivation: 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. Results: The distribution of positions in the CGR plane were shown to be a generalization of Markov chain probability tables that accommodates non-integer orders. Therefore, Markov models are particular cases of CGR models rather than the reverse, as currently accepted. In addition, the CGR generalization has both practical (computational efficiency) and fundamental (scale independence) advantages. These results are illustrated by using Escherichia coli K-12 as a test data-set, in particular, the genes thrA, thrB and thrC of the threonine operon.
Year
DOI
Venue
2001
10.1093/bioinformatics/17.5.429
BIOINFORMATICS
Keywords
Field
DocType
markov model,nucleotides,web pages,dna sequence,genome sequence,amino acid,escherichia coli,markov chain
Web page,Iterative method,Markov model,Computer science,Markov chain,Algorithm,Genomics,Chaos game representation,Sequence modeling,Bioinformatics,Web site
Journal
Volume
Issue
ISSN
17
5
1367-4803
Citations 
PageRank 
References 
56
5.14
1
Authors
5
Name
Order
Citations
PageRank
Jonas S Almeida173142.25
João A. Carriço210510.63
António Maretzek3635.72
Peter A. Noble4565.14
Madilyn Fletcher5565.14