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Zenodo
2026
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| Online-Zugang: | https://doi.org/10.5281/zenodo.19063008 |
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| _version_ | 1866901164338970624 |
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| author | Diel, Eric |
| author_facet | Diel, Eric |
| contents | <p>Biological systems encode and process vast amounts of information while operating under strict energetic, temporal, and molecular fidelity constraints. Although the combinatorial space of possible genomes, regulatory networks, and molecular configurations is astronomically large, only a small and highly structured subset is realized in nature. This work introduces a constraint-based framework for biological organization based on the concept of dynamic realizability. We formalize biological systems as state-space processes and distinguish between the nominal configuration space <span><span>Ω</span><span><span><span>Ω</span></span></span></span> and a dynamically realizable subspace <span><span>ΩR(t)⊂Ω</span><span><span><span>Ω<span><span><span><span><span><span><span>R</span></span></span></span></span></span></span></span><span>(</span><span>t</span><span>)</span><span>⊂</span></span><span><span>Ω</span></span></span></span> defined by feasibility constraints.</p> <p>We derive structural inequalities linking genome length, mutation rate, regulatory network depth, and energetic availability. These constraints collectively define a bounded region of sustainable biological organization and imply that biological complexity is intrinsically limited by coupled energetic, fidelity, and coordination requirements. The framework predicts scaling relationships across taxa, including inverse coupling between genome size and mutation rate and finite ceilings on regulatory depth.</p> <p>Rather than replacing existing theories, this work introduces a higher-level constraint layer governing which biological configurations can persist. The framework generates falsifiable predictions and provides a foundation for empirical investigation of feasibility limits in biological systems.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19063008 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Dynamic Realizability Constraints in Biological Information Systems: A Constraint-Based Framework for Biological Organization Diel, Eric <p>Biological systems encode and process vast amounts of information while operating under strict energetic, temporal, and molecular fidelity constraints. Although the combinatorial space of possible genomes, regulatory networks, and molecular configurations is astronomically large, only a small and highly structured subset is realized in nature. This work introduces a constraint-based framework for biological organization based on the concept of dynamic realizability. We formalize biological systems as state-space processes and distinguish between the nominal configuration space <span><span>Ω</span><span><span><span>Ω</span></span></span></span> and a dynamically realizable subspace <span><span>ΩR(t)⊂Ω</span><span><span><span>Ω<span><span><span><span><span><span><span>R</span></span></span></span></span></span></span></span><span>(</span><span>t</span><span>)</span><span>⊂</span></span><span><span>Ω</span></span></span></span> defined by feasibility constraints.</p> <p>We derive structural inequalities linking genome length, mutation rate, regulatory network depth, and energetic availability. These constraints collectively define a bounded region of sustainable biological organization and imply that biological complexity is intrinsically limited by coupled energetic, fidelity, and coordination requirements. The framework predicts scaling relationships across taxa, including inverse coupling between genome size and mutation rate and finite ceilings on regulatory depth.</p> <p>Rather than replacing existing theories, this work introduces a higher-level constraint layer governing which biological configurations can persist. The framework generates falsifiable predictions and provides a foundation for empirical investigation of feasibility limits in biological systems.</p> |
| title | Dynamic Realizability Constraints in Biological Information Systems: A Constraint-Based Framework for Biological Organization |
| url | https://doi.org/10.5281/zenodo.19063008 |