Modular decomposition and analysis of biological networks

TL;DR

This paper presents a modular decomposition approach for biological networks, enabling analysis of their dynamic behavior through individual modules, which simplifies understanding complex biochemical systems.

Contribution

It introduces a novel modular decomposition method that preserves dynamic properties and isolates parameter effects, facilitating biological network analysis.

Findings

Decomposition preserves network dynamics upon interconnection.

Parameter changes affect only individual modules.

Behavior of complex networks can be inferred from modules.

Abstract

This paper addresses the decomposition of biochemical networks into functional modules that preserve their dynamic properties upon interconnection with other modules, which permits the inference of network behavior from the properties of its constituent modules. The modular decomposition method developed here also has the property that any changes in the parameters of a chemical reaction only affect the dynamics of a single module. To illustrate our results, we define and analyze a few key biological modules that arise in gene regulation, enzymatic networks, and signaling pathways. We also provide a collection of examples that demonstrate how the behavior of a biological network can be deduced from the properties of its constituent modules, based on results from control systems theory.