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Mathematical Characterization of Chaos Game Representation New Algorithms for Nucleotide Sequence Analysis

IR@IICB: CSIR-Indian Institute of Chemical Biology, Kolkata


Field	Value

Title	Mathematical Characterization of Chaos Game Representation New Algorithms for Nucleotide Sequence Analysis

Creator	Dutta, Chitra Das, Jyotirmoy

Subject	Structural Biology & Bioinformatics

Description	Chaos Game Representation (CGR) can recognize patterns in the nueleotide sequences, obtained from databases, of a class of genes using the techniques of fractal structures and by considering DNA sequences as strings composed of four units, G, A, T and C. Such recognition of patterns relies only on visual identification and no mathematical characterization of CGR is known. The present report describes two algorithms that can predict the presence or absence of a stretch of nucleotides in any gene family. The first algorithm can be used to generate DNA sequences represented by any point in the CGR. The second algorithm can simulate known CGR patterns for different gene families by setting the probabilities of occurrence of different di- or trinucleotides by a trial and error process using some guidelines and approximate rules-of-thumb. The validity of the second algorithm has been tested by simulating sequences that can mimic the CGRs of vertebrate non-oncogenes, proto-oncogenes and oncogenes. These algorithms can provide a mathematical basis of the CGR patterns obtained using nucleotide sequences from databases

Publisher	Elsevier

Date	1992

Type	Article PeerReviewed

Format	application/pdf

Identifier	http://www.eprints.iicb.res.in/1796/1/JOURNAL_OF_MOLECULAR_BIOLOGY__228____(3_)_715%2D719;1992[1].pdf Dutta, Chitra and Das, Jyotirmoy (1992) Mathematical Characterization of Chaos Game Representation New Algorithms for Nucleotide Sequence Analysis. Journal of Molecular Biology, 228 (3). pp. 715-719.

Relation	http://dx.doi.org/10.1016/0022-2836(92)90857-G http://www.eprints.iicb.res.in/1796/