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Area of Science:

  • Code Biology
  • Systems Biology
  • Bioinformatics

Background:

  • Biological information flow relies on complex interactions between genetic and epigenetic layers.
  • Existing frameworks struggle to fully capture the dynamic interplay of biological information.
  • The concept of a 'metacode' offers a new perspective on how organisms manage information.

Purpose of the Study:

  • To introduce and define the 'metacode' as a unifying framework for biological information.
  • To integrate genomic and epigenomic data using evidence from large-scale projects.
  • To explore how this metacode facilitates information flow and biological complexity.

Main Methods:

  • Integration of data from ENCODE (phase 3), psychENCODE, and GTEx projects.
  • Analysis of the principles underlying the metacode structure and function.
  • Mapping between constrained regulatory elements and continuous phenotypic spaces.

Main Results:

  • The metacode framework describes intertwined molecular/functional landscapes linked by adaptors.
  • It demonstrates a transition from constrained elements (e.g., regulatory sites) to flexible phenotypic spaces.
  • Biological systems act as informatic attractors navigating an energy metaspace.

Conclusions:

  • The metacode provides a novel lens for understanding the continuous, inter-layered information flow in biological systems.
  • This framework highlights the balance between complexity and noise in emergent biological niches.
  • Code biology offers a new domain for studying biological systems as dynamic, information-driven entities.