A novel quantum algorithm for efficient attractor search in gene regulatory networks.

ABSTRACT: Describing gene interactions in cells is challenging due to their complexity and the limited microscopic detail available. Boolean networks offer a powerful, coarse-grained approach to modeling these dynamics using binary agents and their interactions. In this context, attractors-stable states of the system-are associated with biological phenotypes, making their identification biologically important. However, traditional computing struggles with the exponential growth of the state space in such models. Here, we present a novel quantum search algorithm for identifying attractors in synchronous Boolean networks, specifically designed for use on quantum computers. The algorithm iteratively suppresses known attractor basins, increasing the probability of detecting new ones. Unlike classical me

SUBMITTER: Rossini M 

PROVIDER: S-EPMC12485557 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature