Agent-based modeling of morphogenetic systems: Advantages and challenges

• Type of Material: Article
• Authors: Chad M. Glen, Emory University; Melissa L. Kemp, Emory University; Eberhard Otto Voit, Emory University
• Language: English
• Date: 2019-03-01
• Publisher: Public Library of Science
• Publication Version: Final Published Version
• Copyright Statement: © 2019 Glen et al
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1371/journal.pcbi.1006577
• Title of Journal or Parent Work: PLoS Computational Biology
• ISSN: 1553-734X
• Volume: 15
• Issue: 3
• Start Page: e1006577
• End Page: e1006577
• Grant/Funding Information: The authors gratefully acknowledge funding from NSF Emergent Behaviors of Integrated Cellular Systems Science and Technology Center (CBET 0939511); and NSF-MCB 1517588 (EOV [PI]); and a graduate research fellowship to CMG from the Natural Sciences and Engineering Research Council of Canada.
• Keywords: CELL-MIGRATION; STEM-CELLS; Biochemical Research Methods; IN-VIVO; SIMULATION; Mathematical & Computational Biology; DYNAMICS; PLURIPOTENCY; Life Sciences & Biomedicine; MECHANISMS; Science & Technology; EXTRACELLULAR-MATRIX; POSITIONAL INFORMATION; Biochemistry & Molecular Biology; PATTERN-FORMATION
• Research Categories: Engineering, Biomedical

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.