Cited by 116Developmental Biology and Gene RegulationMathematical Biology Tumor GrowthCellular Mechanics and Interactions

Agent-based modeling of morphogenetic systems: advantages and challenges.

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Glen, Chad M., Kemp, Melissa L., Voit, Eberhard O.·2019·PLoS Computational Biology

Abstract

The complexity of morphogenesis poses a fundamental challenge to understanding the mechanisms governing the formation of biological patterns and structures. Over the past century, numerous processes have been identified as critically contributing to morphogenetic events, but the interplay between the various components and aspects of pattern formation have been much harder to grasp. The combination of traditional biology with mathematical and computational methods has had a profound effect on our current understanding of morphogenesis and led to significant insights and advancements in the field. In particular, the theoretical concepts of reaction-diffusion systems and positional information, proposed by Alan Turing and Lewis Wolpert, respectively, dramatically influenced our general view of morphogenesis, although typically in isolation from one another. In recent years, agent-based modeling has been emerging as a consolidation and implementation of the two theories within a single framework. Agent-based models (ABMs) are unique in their ability to integrate combinations of heterogeneous processes and investigate their respective dynamics, especially in the context of spatial phenomena. In this review, we highlight the benefits and technical challenges associated with ABMs as tools for examining morphogenetic events. These models display unparalleled flexibility for studying various morphogenetic phenomena at multiple levels and have the important advantage of informing future experimental work, including the targeted engineering of tissues and organs.

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  1. [8]Wolpert L. Positional Information In: eLS. Chichester: John Wiley & Sons; 2016 http://www.els.net.
  2. [28]Murray JD. Biomathematics. Berlin: Springer-Verlag; 1990.
  3. [29]Voit EO. Modelltheoretische Untersuchungen zur Anordnung der Knospennarben auf der Oberfläche von Hefezellen [dissertation]. Universität zu Köln; 1981.

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Authors
Glen, C. M., Kemp, M. L., & Voit, E. O.
Affiliations
Georgia Institute of Technology (US)
Corresponding author
  • Kemp, Melissa L.
  • Voit, Eberhard O.
Venue
PLoS Computational Biology
Published
2019-03-28
Volume
15
Issue
3
Pages
e1006577
ISSN
  • 1553-734X (ISSN-L)
  • 1553-7358
OpenAlex
W2923643932
Cited by
116
References
157
Citations by year
2026: 10 · 2025: 17 · 2024: 14 · 2023: 19 · 2022: 15 · 2021: 15 · 2020: 17 · 2019: 8 · 2017: 1
FWCI
1.21
Type
journal article
Language
en
Open access
Locations
  • PLoS Computational Biology (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Science Foundation (0939511, 1517588)
  • Emergent Behaviors of Integrated Cellular Systems (0939511)
  • Natural Sciences and Engineering Research Council of Canada
  • Division of Chemical, Bioengineering, Environmental, and Transport Systems (CBET-0939511, 0939511)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
  • Physical Sciences › Mathematics › Modeling and Simulation › Mathematical Biology Tumor Growth
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Cellular Mechanics and Interactions
Keywords
morphogenesis, agent-based modeling, reaction-diffusion systems, positional information, Turing patterns, biological pattern formation, morphogenetic systems, tissue engineering, computational modeling of development
MeSH terms
Models, Biological, Morphogenesis, Systems Analysis, Apoptosis, Cell Proliferation

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