# Marker and source-marker reprogramming of Most Permissive Boolean networks and ensembles with BoNesis

arXiv: https://arxiv.org/abs/2207.13307 · HTML: https://mlsanity.com/paper/2207.13307/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 28 references that are in the map.
- First posted on arXiv 27 Jul 2022.

## Builds on (most cited first, 1 of 1)

- [Synthesis of Boolean Networks from Biological Dynamical Constraints using Answer-Set Programming](https://mlsanity.com/paper/1909.04309/) (2019)

## Built on by (most cited first, 2 of 2)

- [Deep Reinforcement Learning for Controlled Traversing of the Attractor Landscape of Boolean Models in the Context of Cellular Reprogramming](https://mlsanity.com/paper/2402.08491/) (2024)
- [Tackling Universal Properties of Minimal Trap Spaces of Boolean Networks](https://mlsanity.com/paper/2305.02442/) (2023)

## Abstract (arXiv)

Boolean networks (BNs) are discrete dynamical systems with applications to the modeling of cellular behaviors. In this paper, we demonstrate how the software BoNesis can be employed to exhaustively identify combinations of perturbations which enforce properties on their fixed points and attractors. We consider marker properties, which specify that some components are fixed to a specific value. We study 4 variants of the marker reprogramming problem: the reprogramming of fixed points, of minimal trap spaces, and of fixed points and minimal trap spaces reachable from a given initial configuration with the most permissive update mode. The perturbations consist of fixing a set of components to a fixed value. They can destroy and create new attractors. In each case, we give an upper bound on their theoretical computational complexity, and give an implementation of the resolution using the BoNesis Python framework. Finally, we lift the reprogramming problems to ensembles of BNs, as supported by BoNesis, bringing insight on possible and universal reprogramming strategies. This paper can be executed and modified interactively.