Compensatory interactions to stabilize multiple steady states or mitigate the effects of multiple deregulations in biological networks

TL;DR

This paper generalizes methods for designing compensatory interactions in Boolean biological network models to stabilize multiple steady states and address multi-node damages, with applications to cancer-related networks.

Contribution

It introduces a generalized approach for stabilizing multiple attractors in Boolean networks under multi-node damage scenarios, expanding previous single-node methods.

Findings

Method successfully stabilizes multiple steady states in biological networks.

Network structure influences resilience and repair strategies.

Applicable to cancer-related intracellular network models.

Abstract

Complex diseases can be modeled as damage to intracellular networks that results in abnormal cell behaviors. Network-based dynamic models such as Boolean models have been employed to model a variety of biological systems including those corresponding to disease. Previous work designed compensatory interactions to stabilize an attractor of a Boolean network after single node damage. We generalize this method to a multinode damage scenario and to the simultaneous stabilization of multiple steady state attractors. We classify the emergent situations, with a special focus on combinatorial effects, and characterize each class through simulation. We explore how the structural and functional properties of the network affect its resilience and its possible repair scenarios. We demonstrate the method's applicability to two intracellular network models relevant to cancer. This work has implications in designing prevention strategies for complex disease.