How can information theory help scientists study biological systems?

In the field of systems biology, scientists adapt concepts from information theory to analyze how biological systems process, transmit, and integrate information. By applying mathematical frameworks originally developed for communication and computing, researchers aim to represent higher-order biological processes—such as gene expression and cellular signaling—from an information-based perspective.1

Information theory provides a conceptual toolkit for modeling biological networks, such as metabolic or developmental pathways. For instance, researchers use these models to study how cells integrate multiple upstream inputs through second messenger molecules to regulate downstream targets. While well-characterized systems like lactose utilization in Escherichia coli have been successfully modeled, scientists face ongoing challenges in accounting for the complex, context-dependent nature of biological information, such as how a cell's metabolic state or external environment influences gene expression.12

Ultimately, the goal is to develop quantitative models that embody hypotheses about the structure and function of biological systems, potentially transforming fields ranging from agriculture to personalized medicine.1