ArticleBiophysics and physicobiology2021
Transfer entropy dependent on distance among agents in quantifying leader-follower relationships.
Article in Biophysics and physicobiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Determination of the latent geometry of atorvastatin pharmacokinetics by transfer entropy to identify bottlenecks.BMC pharmacology & toxicology · 2025Article
- Metareview: a survey of active matter reviews.The European physical journal. E, Soft matter · 2025Review
- Inferring the roles of individuals in collective systems using information-theoretic measures of influence.Biophysics and physicobiology · 2024Review
- Analysis of the singularity cells controlling the pattern formation in multi-cellular systems.Biophysics and physicobiology · 2024Article
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Authors and funding
5 authors.
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Abstract
Synchronized movement of (both unicellular and multicellular) systems can be observed almost everywhere. Understanding of how organisms are regulated to synchronized behavior is one of the challenging issues in the field of collective motion. It is hypothesized that one or a few agents in a group regulate(s) the dynamics of the whole collective, known as leader(s). The identification of the leader (influential) agent(s) is very crucial. This article reviews different mathematical models that represent different types of leadership. We focus on the improvement of the leader-follower classification problem. It was found using a simulation model that the use of interaction domain information significantly improves the leader-follower classification ability using both linear schemes and information-theoretic schemes for quantifying influence. This article also reviews different schemes that can be used to identify the interaction domain using the motion data of agents.
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