Publication Title
IEEE Transactions on Molecular, Biological, and Multi-scale Communications
Document Type
Article
Abstract/Description
Engineers have developed abstract network models to better understand the recurring problems faced by communication systems. This paper argues that these models can be generalized to describe biological communications systems given that they share many requirements with human-designed systems, including functional requirements and physical constraints. Leveraging collaboration, biologists and engineers can work together to use well-understood communication systems, designed to carry data across a computer network, as a model for analyzing less well-understood biological communication systems in order to make predictions and uncover previously unknown functionalities. To illustrate this approach, we apply the Recursive Internet Network Architecture model (RINA) to two biological communications systems: DNA-to-ribosome signaling and phosphorylation signaling in bacterial chemotaxis. The RINA model categorizes biological observations as solutions to the familiar design requirements of multiplexing, marshaling, error control, and flow control. This approach offers a structured framework for analyzing biological communication systems that yields new insights into why they are structured as they are and how to further explore them.
Department
Engineering and Technology
DOI
10.1109/TMBMC.2025.3625536
ISSN
2372-2061
Date
2025
Citation Information
White, Russ; Brown Reeves, Emily; and Fudge, Gerald L., "Using Network Models to Understand Biological Signaling Architecture" (2025). Faculty Publications. 245.
https://lair.etamu.edu/cose-faculty-publications/245
