Speaker
Description
A central challenge in systems biology is understanding how gene regulatory networks (GRNs) coordinate cellular decision-making within complex topological structures. This study introduces a framework to quantify the alignment of regulatory logic among interacting genes, a property defined here as structural coherence. By applying this metric, we identify "teams”, functionally coupled gene sets that exhibit cooperative activation. We investigate the topological implications of structural coherence by characterizing how team size and composition scale with key network features. To link architecture with dynamical behavior, we employ a threshold Boolean model, specifically a probabilistic Ising model, to evaluate the relationship between structural coherence and gene expression coordination. Our results demonstrate that structurally coherent groups significantly influence the configuration and stability of network attractors. Furthermore, analysis of biological GRNs shows how hierarchical organization enables coherent decision-making to scale across large gene assemblies, even in the presence of localized incoherence. The structural coherence framework provides a robust, generalizable tool that integrates local interactions and global network architecture to explain the emergent regulatory coordination.
