Systematizing Cellular Complexity: A Hilbertian Approach To Biological Problems

TL;DR

This paper proposes a formal, Hilbertian framework to systematically understand cellular complexity, integrating components into a comprehensive system-level map that accounts for nonlinearities, noise, and causal dynamics.

Contribution

It introduces a novel Hilbertian approach to formalize and axiomatize key biological problems, bridging abstract theory and cellular mechanisms.

Findings

Highlights the importance of system-level formalization in biology

Provides a framework for understanding cellular robustness and adaptability

Connects theoretical models with biological phenomena

Abstract

Examining individual components of cellular systems has been successful in uncovering molecular reactions and interactions. However, the challenge lies in integrating these components into a comprehensive system-scale map. This difficulty arises due to factors such as missing links (unknown variables), overlooked nonlinearities in high-dimensional parameter space, downplayed natural noisiness and stochasticity, and a lack of focus on causal influence and temporal dynamics. Composite static and phenomenological descriptions, while appearing complicated, lack the essence of what makes the biological systems truly "complex". The formalization of system-level problems is therefore important in constructing a meta-theory of biology. Addressing fundamental aspects of cellular regulation, adaptability, and noise management is vital for understanding the robustness and functionality of biological systems. These aspects encapsulate the challenges that cells face in maintaining stability, responding to environmental changes, and harnessing noise for functionality. This work examines these key problems that cells must solve, serving as a template for such formalization and as a step towards the axiomatization of biological investigations. Through a detailed exploration of cellular mechanisms, particularly homeostatic configuration, ion channels and harnessing noise, this paper aims to illustrate complex concepts and theories in a tangible context, providing a bridge between abstract theoretical frameworks and concrete biological phenomena.