Edinburgh Research Explorer

Agent-based modelling of Pattern Formation in Pluripotent Stem Cells: Initial Experiments and Results

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationProceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018
EditorsQingli Li, Wei Li, Lipo Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538676042
DOIs
Publication statusPublished - 1 Feb 2019
Event11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018 - Beijing, China
Duration: 13 Oct 201815 Oct 2018

Conference

Conference11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018
CountryChina
CityBeijing
Period13/10/1815/10/18

Abstract

The underlying mechanisms of pluripotent stem cell behaviours are complicated and not fully understood. However, this need not be a barrier to prediction of pattern formation in colonies of cells if a high-level model of their social interaction decisions gives sufficient predictive power. This is analogous to prediction of behaviours in crowds of people, where we cannot model individuals in detail, but we can predict aggregate crowd behaviour from comparatively simple agent-based models of their social conventions. In this research, agent-based modelling was applied to study pattern formation in pluripotent stem cells. The aim of this study is to develop a modelling approach towards investigating the social and dynamic behaviours of pluripotent stem cells from their high-level features. We establish six agent-based models with different behavioural protocols and present the results of a set of experiments. Simulated experiments provide evidence of potential behavioural rules of stem cells. This study provides an intuitive framework for the investigation of social pattern behaviours in pluripotent stem cells.

    Research areas

  • agent-based model, pattern formation, pluripotent stem cells

ID: 118984915