Information processing in living systems

TL;DR

This paper reviews how information theory is applied to understand biological systems, from molecules to groups, highlighting measurements of information flow and evidence of evolutionary optimization.

Contribution

It synthesizes diverse studies demonstrating the application of information theory to biological networks and discusses evidence for evolutionary optimization of information processing.

Findings

Information flow can be directly measured in biological networks.

Biological systems may have evolved to optimize information gathering.

Information theoretic analysis spans from molecules to groups of organisms.

Abstract

Life depends as much on the flow of information as on the flow of energy. Here we review the many efforts to make this intuition precise. Starting with the building blocks of information theory, we explore examples where it has been possible to measure, directly, the flow of information in biological networks, or more generally where information theoretic ideas have been used to guide the analysis of experiments. Systems of interest range from single molecules (the sequence diversity in families of proteins) to groups of organisms (the distribution of velocities in flocks of birds), and all scales in between. Many of these analyses are motivated by the idea that biological systems may have evolved to optimize the gathering and representation of information, and we review the experimental evidence for this optimization, again across a wide range of scales.