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The cellular computer DNA: program or data.

H Atlan1, M Koppel

  • 1Dept of Biophysics, Hadassah Medical Center, Jerusalem, Israel.

Bulletin of Mathematical Biology
|January 1, 1990
PubMed
Summary
This summary is machine-generated.

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The classical genetic program metaphor is challenged by algorithmic complexity. DNA is reframed as data within a parallel computing network, suggesting an evolving network model for cellular processes.

Area of Science:

  • Computational Biology
  • Genetics
  • Theoretical Computer Science

Background:

  • The traditional view of DNA as a static genetic program is widely accepted.
  • Recent advancements in algorithmic complexity and program/data properties offer new analytical tools.

Purpose of the Study:

  • To critically re-evaluate the explanatory power of the genetic program metaphor for DNA.
  • To explore alternative conceptual frameworks for understanding DNA's function within the cell.

Main Methods:

  • Analysis of algorithmic complexity and logical properties of computational programs and data.
  • Investigation of structural string properties applicable to DNA sequences.
  • Application of the concept of 'sophistication' to quantify meaningful complexity.

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Main Results:

  • The classical metaphor's limitations are highlighted when considering DNA's structural and computational properties.
  • A distinction between 'program' and 'data' becomes relevant for DNA analysis.
  • An alternative metaphor of DNA as data in a parallel computing network is proposed.

Conclusions:

  • DNA's function may be better understood as data processed by a cellular computing network.
  • This network is embedded within the cell's global geometrical and biochemical structure.
  • An evolving network model, where outputs influence network structure over time, is the most plausible framework.