Inferring the roles of individuals in collective systems using information-theoretic measures of influence

Sulimon Sattari; Udoy S Basak; M Mohiuddin; Mikito Toda; Tamiki Komatsuzaki

doi:10.2142/biophysico.bppb-v21.s014

Inferring the roles of individuals in collective systems using information-theoretic measures of influence

Biophys Physicobiol. 2024 Mar 22;21(Supplemental):e211014. doi: 10.2142/biophysico.bppb-v21.s014. eCollection 2024.

Authors

Sulimon Sattari¹, Udoy S Basak², M Mohiuddin^{3

4}, Mikito Toda^{1

5

6}, Tamiki Komatsuzaki^{1

3

7

8

9}

Affiliations

¹ Research Institute for Electronic Science, Hokkaido University, Sapporo, Hokkaido 001‑0020, Japan.
² Pabna University of Science and Technology, Pabna 6600, Bangladesh.
³ Graduate School of Chemical Sciences and Engineering, Hokkaido University, Sapporo, Hokkaido 060‑0812, Japan.
⁴ Comilla University, Cumilla 3506, Bangladesh.
⁵ Faculty Division of Natural Sciences, Nara Women's University, Nara 630‑8506, Japan.
⁶ Graduate School of Information Science, University of Hyogo, Kobe, Hyogo 650‑0047, Japan.
⁷ Institute for Chemical Reaction Design and Discovery (WPI‑ICReDD), Hokkaido University, Sapporo, Hokkaido 001‑0021, Japan.
⁸ Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Osaka 565‑0871, Japan.
⁹ The Institute of Scientific and Industrial Research, Osaka University, Osaka, Ibaraki 567‑0047, Japan.

Abstract

In collective systems, influence of individuals can permeate an entire group through indirect interactionscom-plicating any scheme to understand individual roles from observations. A typical approach to understand an individuals influence on another involves consideration of confounding factors, for example, by conditioning on other individuals outside of the pair. This becomes unfeasible in many cases as the number of individuals increases. In this article, we review some of the unforeseen problems that arise in understanding individual influence in a collective such as single cells, as well as some of the recent works which address these issues using tools from information theory.

Keywords: causal inference; data-driven approach; information theory; single cells collectives; transfer entropy.

2024 THE BIOPHYSICAL SOCIETY OF JAPAN.

Publication types

Review