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Central Dogma Cycle and Network: A Model for Cell Memory.

Martin R Schiller1,2

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PubMed
Summary
This summary is machine-generated.

This study introduces the Central Dogma cycle (CDC) and network (CDCN) to explain cellular memory and information flow beyond DNA. This dynamic model reframes heredity and evolution as network optimization.

Keywords:
Central Dogmacycledigital logicmemorynetwork

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Area of Science:

  • Molecular Biology
  • Systems Biology
  • Computational Biology

Background:

  • The traditional Central Dogma of molecular biology explains genetic information flow but is insufficient for cellular memory and decision-making.
  • Existing models do not fully capture the dynamic, cyclical nature of biological information processing within cells.

Purpose of the Study:

  • To propose an extended model, the Central Dogma cycle (CDC) and Central Dogma cyclic network (CDCN), to better explain cellular memory and information management.
  • To reframe heredity and evolution within a network optimization framework.
  • To provide a unified perspective on cellular processes, adaptation, and disease pathology.

Main Methods:

  • Conceptual model development extending the Central Dogma.
  • Incorporation of protein folding, networking, metabolic, and signaling pathways.
  • Analogies drawn to computer memory functions (input, read, write, execute, erase).

Main Results:

  • The proposed Central Dogma cycle (CDC) highlights the cyclical nature of biological information flow, including protein folding and networking.
  • The Central Dogma cyclic network (CDCN) integrates metabolic and signaling pathways as logic-enabled processors linking genotype to phenotype.
  • This cyclic network model offers a new perspective on cellular memory, heredity, and evolution.

Conclusions:

  • The Central Dogma cycle (CDC) and network (CDCN) provide a more comprehensive framework for understanding cellular information processing, memory, and decision-making.
  • This model reframes heredity beyond nucleic acid sequences and evolution as the optimization of memory-bearing networks.
  • The CDCN model offers a unified view of biological systems, from cellular processes to disease pathology.