Aguilar et al.
Aguilar B, Fang P, Laubenbacher R, Murrugarra D
2020 · Letters in biomathematics
One of the ultimate goals in systems biology is to develop control strategies to find efficient medical treatments.
Abstract
From the original paper, Letters in biomathematics · PubMed
One of the ultimate goals in systems biology is to develop control strategies to find efficient medical treatments. One step towards this goal is to develop methods for changing the state of a cell into a desirable state. We propose an efficient method that determines combinations of network perturbations to direct the system towards a predefined state. The method requires a set of control actions such as the silencing of a gene or the disruption of the interaction between two genes. An optimal control policy defined as the best intervention at each state of the system can be obtained using existing methods. However, these algorithms are computationally prohibitive for models with tens of nodes. Our method generates control actions that approximates the optimal control policy with high probability with a computational efficiency that does not depend on the size of the state space. Our C++ code is available at https://github.com/boaguilar/SDDScontrol.
Summary
Editorial summary pending review by the maintainer. The paper's own abstract appears above; the Atlas summary in the maintainer's voice will explain how Aguilar et al. relates to the cross-modality inverse-design framework of the review.
Why this level
Level 3 because candidate interventions enter an explicit forward operator and the predicted post-intervention outcome is what scores each candidate. Representation family is executable intervention model. Cited in §3.4 of the review. Editorial rationale pending review by the maintainer.