Thermodynamics of statistical inference by cells

Area of Science:

• Thermodynamics
• Information Theory
• Biochemistry
• Statistical Inference

Background:

• The interplay between thermodynamics, computation, and information is well-established.
• Biochemical signaling networks are crucial for cellular function and information processing.

Purpose of the Study:

• To investigate the thermodynamic constraints on statistical estimation and learning.
• To determine how thermodynamics limits the accuracy of biochemical signaling networks in estimating external signal concentrations.

Main Methods:

• Analysis of (nonequilibrium) thermodynamics.
• Modeling of biochemical signaling networks' estimation capabilities.

Main Results:

• Thermodynamic principles impose fundamental limits on statistical inference.
• The accuracy of signal concentration estimation by biochemical networks is constrained by energy consumption.

Conclusions:

• Energy consumption is a critical factor limiting the precision of statistical inference in biological systems.
• Fundamental thermodynamic constraints govern the capabilities of learning and estimation in biochemical networks.