Thermodynamics of statistical inference by cells

TL;DR

This paper explores how thermodynamic principles fundamentally limit the accuracy of cellular biochemical networks in estimating external signals, linking energy consumption to statistical inference constraints.

Contribution

It extends thermodynamic concepts to show fundamental limits on biological statistical estimation and learning within cells.

Findings

Accuracy of cellular estimation is constrained by energy consumption.

Thermodynamic constraints limit the precision of biochemical signaling.

Fundamental energy-accuracy trade-offs in cellular information processing.

Abstract

The deep connection between thermodynamics, computation, and information is now well established both theoretically and experimentally. Here, we extend these ideas to show that thermodynamics also places fundamental constraints on statistical estimation and learning. To do so, we investigate the constraints placed by (nonequilibrium) thermodynamics on the ability of biochemical signaling networks within cells to estimate the concentration of an external signal. We show that accuracy is limited by energy consumption, suggesting that there are fundamental thermodynamic constraints on statistical inference.