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SEGMENT: identifying compositional domains in DNA sequences.

J L Oliver1, R Román-Roldán, J Pérez

  • 1Department of Genetics, Faculty of Sciences, University of Granada, Spain. oliver@ugr.es

Bioinformatics (Oxford, England)
|April 4, 2000
PubMed
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This study introduces a new algorithm for analyzing DNA sequence composition. The SEGMENT program identifies homogeneous domains and measures sequence compositional complexity (SCC) for a multiscale view.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • DNA sequences exhibit compositional heterogeneity, often with fractal structures.
  • Detecting complex compositional patterns in DNA is challenging with current methods.
  • A computationally efficient segmentation method using Jensen-Shannon entropic divergence has been proposed.

Purpose of the Study:

  • To develop and implement a heuristic segmentation algorithm for DNA sequences.
  • To create a Windows-based program (SEGMENT) for analyzing DNA compositional structure.
  • To derive a global measure of sequence compositional complexity (SCC).

Main Methods:

  • A heuristic segmentation algorithm was developed.
  • The SEGMENT program implements a local optimization procedure for domain identification.

Related Experiment Videos

  • Sequence compositional complexity (SCC) is calculated based on domain properties.

    • Main Results:

    • The SEGMENT program successfully divides DNA sequences into homogeneous domains.
    • A global measure of sequence compositional complexity (SCC) was derived.
    • SCC is computed as a function of significance level, offering a multiscale analysis.

    Conclusions:

    • The developed algorithm and SEGMENT program provide a novel approach to analyze DNA sequence heterogeneity.
    • The method allows for a multiscale assessment of sequence compositional complexity.
    • This tool aids in understanding the fractal structure of DNA sequences.