Amoebic foraging model of metastatic cancer cells

Daiki Andoh, Yukio Pegio Gunji

Research output: Contribution to journalArticlepeer-review

Abstract

The Lévy walk is a pattern that is often seen in the movement of living organisms; it has both ballistic and random features and is a behavior that has been recognized in various animals and unicellular organisms, such as amoebae, in recent years. We proposed an amoeba locomotion model that implements Bayesian and inverse Bayesian inference as a Lévy walk algorithm that bal-ances exploration and exploitation, and through a comparison with general random walks, we con-firmed its effectiveness. While Bayesian inference is expressed only by P(h) = P(h|d), we introduce inverse Bayesian inference expressed as P(d|h) = P(d) in a symmetry fashion. That symmetry con-tributes to balancing contracting and expanding the probability space. Additionally, the conditions of various environments were set, and experimental results were obtained that corresponded to changes in gait patterns with respect to changes in the conditions of actual metastatic cancer cells.

Original languageEnglish
Article number1140
JournalSymmetry
Volume13
Issue number7
DOIs
Publication statusPublished - 2021 Jul

Keywords

  • Amoebic motion
  • Bayesian inference
  • Inverse Bayesian inference
  • Lévy walk
  • Metastatic cancer cells

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Chemistry (miscellaneous)
  • Mathematics(all)
  • Physics and Astronomy (miscellaneous)

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