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Proceedings Paper

Application of chaos game representation method to visualize genome structure
Author(s): Alain Giron; Bernard Fertil; Djamel Brahmi; Joseph Vilain; Patrick Deschavanne
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Paper Abstract

The recent availability of long and even complete genomic sequences opens a new field of research devoted to the general analysis of their global structure, without regard to gene interpretation. The exploration of such huge sequences (up to several megabases) needs new kind of data representation, allowing immediate visual interpretation of genomic structure and giving insights into the underlying mechanisms ruling it. Our approach takes advantages of the CGR (Chaos Game Representation) for creating images of large genomic sequences. The CGR method, modified here to allow for quantification, is an algorithm that produces pictures displaying frequencies of words (small sequences of the four nucleotides: G, A, T, C) and revealing nested patterns in DNA sequences. It is proved to be a quick and robust method to extract information from long DNA sequences allowing comparisons of sequences and detection of anomalies in frequency of words. Each species seems to be associated to a specific CGR image, which can therefore be considered as a genomic signature.

Paper Details

Date Published: 25 March 1999
PDF: 9 pages
Proc. SPIE 3643, Visual Data Exploration and Analysis VI, (25 March 1999); doi: 10.1117/12.342846
Show Author Affiliations
Alain Giron, INSERM (France)
Bernard Fertil, INSERM (France)
Djamel Brahmi, INSERM (France)
Joseph Vilain, INSERM (France)
Patrick Deschavanne, INSERM (France)

Published in SPIE Proceedings Vol. 3643:
Visual Data Exploration and Analysis VI
Robert F. Erbacher; Philip C. Chen; Craig M. Wittenbrink, Editor(s)

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