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Encoding and Decoding DNA Sequences by Integer Chaos Game Representation.

Changchuan Yin1

  • 1Department of Mathematics, Statistics, and Computer Science, The University of Illinois at Chicago , Chicago, Illinois.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|December 6, 2018
PubMed
Summary
This summary is machine-generated.

We introduce a new integer chaos game representation (iCGR) for DNA sequences. This method uniquely encodes DNA using three integers, enabling lossless compression and novel sequence analysis.

Keywords:
DNA sequenceschaos game representationcompressiondecodingencoding

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Area of Science:

  • Bioinformatics
  • Genomics
  • Computational Biology

Background:

  • DNA sequences encode genetic information, containing hidden signals discoverable through numerical transformation.
  • Current numerical representations of DNA have limitations for genomic signal compression, encryption, and steganography.

Purpose of the Study:

  • To propose a novel integer chaos game representation (iCGR) for DNA sequences.
  • To develop a lossless encoding method for DNA sequences using the iCGR.

Main Methods:

  • Representing DNA sequences via an iterated function of nucleotides and their positions.
  • Encoding and recovering DNA sequences using three integers: sequence length and two accumulated nucleotide distribution values.

Main Results:

  • The iCGR method provides a unique integer representation of DNA sequences.
  • The integer encoding scheme achieves lossless compression of approximately 2 bits per nucleotide.

Conclusions:

  • The integer chaos game representation offers a novel and efficient method for DNA sequence encoding.
  • iCGR is a prospective tool for advanced sequence analysis, compression, encryption, and steganography.