Step-wise target controllability identifies dysregulated pathways of macrophage networks in multiple sclerosis

Giulia Bassignana (1) , Jennifer Fransson (2) , Vincent Henry (1) , Olivier Colliot (1) , Violetta Zujovic (2) , Fabrizio de Vico Fallani (1)

1 ARAMIS - Algorithms, models and methods for images and signals of the human brain = Algorithmes, modèles et méthodes pour les images et les signaux du cerveau humain [ICM Paris]
2 ICM - Institut du Cerveau = Paris Brain Institute

Identifying the nodes able to drive the state of a network is crucial to understand, and eventually control, biological systems. Despite recent advances, such identification remains difficult because of the huge number of equivalent controllable configurations, even in relatively simple networks. Based on the evidence that in many applications it is essential to test the ability of individual nodes to control a specific target subset, we develop a fast and principled method to identify controllable driver-target configurations in sparse and directed networks. We demonstrate our approach on simulated networks and experimental gene networks to characterize macrophage dysregulation in human subjects with multiple sclerosis.

Mots clés: Network controllability; Molecular networks; Multiple sclerosis; Neural disease

Domaines: Mathématiques [math]; Sciences du Vivant [q-bio]

Giulia Bassignana, Jennifer Fransson, Vincent Henry, Olivier Colliot, Violetta Zujovic, et al.. Step-wise target controllability identifies dysregulated pathways of macrophage networks in multiple sclerosis. Network Neuroscience, 2021, 5 (2), pp.337-357. ⟨10.1162/netn_a_00180⟩. ⟨hal-03022314⟩