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Special factors in biological strings.

A Colosimo1, A De Luca

  • 1Dipartimento di Scienze Biochimiche, Università di Roma "La Sapienza", Piazzale A. Moro 2, Roma, 00185, Italy.

Journal of Theoretical Biology
|April 25, 2000
PubMed
Summary
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Biological macromolecules like DNA and RNA are analyzed as sequences. Their special factor distributions differ significantly from random sequences, regardless of length or origin.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Biological macromolecules, including DNA, RNA, and proteins, can be conceptualized as finite sequences over a defined alphabet.
  • This study focuses on DNA and RNA sequences, treating them as words composed of a four-letter alphabet.

Purpose of the Study:

  • To compare biological DNA/RNA sequences (or fragments) with random sequences and shuffled versions of themselves.
  • To develop and apply combinatorial techniques for analyzing finite words (sequences).
  • To investigate the role of 'special factors' in distinguishing biological sequences from random ones.

Main Methods:

  • Development of combinatorial analysis techniques for finite words.
  • Comparison of statistical properties of special factors in biological DNA/RNA sequences versus random or shuffled sequences.

Related Experiment Videos

  • Analysis of sequence fragments across various lengths (<2650 bp) and phylogenetic origins.

    • Main Results:

    • A distinct and typical difference was observed in the distribution of right and left special factors between analyzed DNA/RNA fragments and random/shuffled sequences.
    • This observed difference was consistent across different sequence lengths within the studied range.
    • The phylogenetic origin of the DNA/RNA fragments did not influence this characteristic difference.

    Conclusions:

    • The distribution patterns of special factors serve as a reliable indicator to differentiate biological DNA/RNA sequences from random sequences.
    • Combinatorial analysis of special factors offers a novel method for sequence characterization.
    • The findings suggest inherent structural or organizational principles in biological sequences that are absent in random or shuffled counterparts.