Beyond the genome: A multi-scale, agent-based taxonomy of biological codes and energetic constraints

Abstract

This work critically examines the organizational principles governing living systems and introduces emerging rules that pave the way for a computational approach to understanding life. It challenges the conventional assumption of the modern synthesis, which claims that the code of life resides solely in DNA, genetic networks, and epigenetics. Instead, we argue that the information essential for sustaining life is distributed across multiple scales. Drawing from diverse frameworks such as cybernetics and machine learning, we propose a fresh perspective on this fundamental question.

We begin by exploring the complexity of life and propose a thoughtfully constructed preliminary taxonomy of biological codes, while recognizing the potential for alternative frameworks. This interpretation integrates speculative ideas from concepts like constraint closure and agent-based modeling, framing the hierarchy of life as governed by a dynamic tension between stability and exploration. Building on this foundation, we analyze the compositional rules and properties of biological codes, uncovering their hierarchical and causal relationships across scales. We emphasize the cell's role as a fundamental cybernetic agent and discuss how this framework contributes to understanding natural phenomena such as cellular differentiation and collaboration.

The theoretical implications of this perspective highlight the importance of emergence and top-down interactions in fostering complexity. We argue that information distributed across multiple scales is necessary but not sufficient for sustaining life because living systems are open and dynamic, relying fundamentally on environmental interactions, subjected to entropy, mass, and energy exchanges. Additionally, any form of life functions as a physical information-processing system, further emphasizing the intricate interplay between structure and environment. We propose that available energy not only sustains autopoiesis in biological systems, but a fraction of it also drives their adaptation and evolution in an exploratory fashion.

Finally, we present a practical example and outline future directions for this approach. Specifically, we illustrate how our framework advances the understanding of protein folding agents, particularly in deciphering their regulatory dynamics and interactions with chaperones and organelles. By bridging theoretical concepts with practical examples, this work seeks to provide a framework for analyzing and manipulating complex biological systems, with potential implications for fields such as systems biology and Artificial Intelligence.