An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems

Hector Zenil; Narsis A Kiani; Francesco Marabita; Yue Deng; Szabolcs Elias; Angelika Schmidt; Gordon Ball; Jesper Tegnér

doi:10.1016/j.isci.2019.07.043

An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems

iScience. 2019 Sep 27:19:1160-1172. doi: 10.1016/j.isci.2019.07.043. Epub 2019 Aug 8.

Authors

Hector Zenil¹, Narsis A Kiani², Francesco Marabita³, Yue Deng⁴, Szabolcs Elias³, Angelika Schmidt³, Gordon Ball³, Jesper Tegnér⁵

Affiliations

¹ Algorithmic Dynamics Lab, Center for Molecular Medicine, Karolinska Institutet, Stockholm 171 76, Sweden; Unit of Computational Medicine, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Solna, Stockholm 171 76, Sweden; Oxford Immune Algorithmics, Reading RG1 3EU, UK; Science for Life Laboratory, Solna 171 65, Sweden; Algorithmic Nature Group, LABORES for the Natural and Digital Sciences, Paris 75006, France. Electronic address: hector.zenil@algorithmicnaturelab.org.
² Algorithmic Dynamics Lab, Center for Molecular Medicine, Karolinska Institutet, Stockholm 171 76, Sweden; Unit of Computational Medicine, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Solna, Stockholm 171 76, Sweden; Science for Life Laboratory, Solna 171 65, Sweden; Algorithmic Nature Group, LABORES for the Natural and Digital Sciences, Paris 75006, France.
³ Unit of Computational Medicine, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Solna, Stockholm 171 76, Sweden; Science for Life Laboratory, Solna 171 65, Sweden.
⁴ Unit of Computational Medicine, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Solna, Stockholm 171 76, Sweden.
⁵ Unit of Computational Medicine, Center for Molecular Medicine, Department of Medicine, Karolinska Institutet, Solna, Stockholm 171 76, Sweden; Science for Life Laboratory, Solna 171 65, Sweden; Biological and Environmental Sciences and Engineering Division, Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Kingdom of Saudi Arabia.

Abstract

We introduce and develop a method that demonstrates that the algorithmic information content of a system can be used as a steering handle in the dynamical phase space, thus affording an avenue for controlling and reprogramming systems. The method consists of applying a series of controlled interventions to a networked system while estimating how the algorithmic information content is affected. We demonstrate the method by reconstructing the phase space and their generative rules of some discrete dynamical systems (cellular automata) serving as controlled case studies. Next, the model-based interventional or causal calculus is evaluated and validated using (1) a huge large set of small graphs, (2) a number of larger networks with different topologies, and finally (3) biological networks derived from a widely studied and validated genetic network (E. coli) as well as on a significant number of differentiating (Th17) and differentiated human cells from a curated biological network data.

Keywords: Algorithms; Complex Systems; Computer Science; Gene Network; Systems Biology.