LBIBCell: a cell-based simulation environment for morphogenetic problems

Tanaka, Simon; Sichau, David; Iber, Dagmar

doi:10.1093/bioinformatics/btv147

Cited by 59 publications

(74 citation statements)

References 40 publications

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“…23), an on-lattice voxel-based model without freely moving components, provides a simulation environment merging the cellular Potts model with chemical fields and diffusion equations. Macroscopic cell behaviours are linked to intracellular molecular concentrations simulated using an external Systems Biology Markup Language (SMBL) library such as libRoadRunner; CellSys24 focuses on multi-agent simulations of tumour growth and LBIBCell25 couples viscoelastic cell mechanics with reaction-advection-diffusion solvers, but neither includes GRN specification.…”

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confidence: 99%

A cell-based computational model of early embryogenesis coupling mechanical behaviour and gene regulation

et al. 2017

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The study of multicellular development is grounded in two complementary domains: cell biomechanics, which examines how physical forces shape the embryo, and genetic regulation and molecular signalling, which concern how cells determine their states and behaviours. Integrating both sides into a unified framework is crucial to fully understand the self-organized dynamics of morphogenesis. Here we introduce MecaGen, an integrative modelling platform enabling the hypothesis-driven simulation of these dual processes via the coupling between mechanical and chemical variables. Our approach relies upon a minimal ‘cell behaviour ontology' comprising mesenchymal and epithelial cells and their associated behaviours. MecaGen enables the specification and control of complex collective movements in 3D space through a biologically relevant gene regulatory network and parameter space exploration. Three case studies investigating pattern formation, epithelial differentiation and tissue tectonics in zebrafish early embryogenesis, the latter with quantitative comparison to live imaging data, demonstrate the validity and usefulness of our framework.

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confidence: 99%

A cell-based computational model of early embryogenesis coupling mechanical behaviour and gene regulation

et al. 2017

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“…[131] Morpheus [130], Simmune [243] and Chaste [132,244]; center-based models: CellSys [150], Chaste [132,244], EPISIM [245], Timothy [246,247] and Biocellion [248], or a deformable cell model: VirtualLeaf [249], LBIBCell [250] and SEM++ [181]. Most of these tools have one or more specific features, such as multi-scale modeling, usability, or performance.…”

Section: Available Tools and Software Development For Modelingmentioning

confidence: 99%

Simulating tissue mechanics with agent-based models: concepts, perspectives and some novel results

et al. 2015

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In this paper we present an overview of agentbased models that are used to simulate mechanical and physiological phenomena in cells and tissues, and we discuss underlying concepts, limitations, and future perspectives of these models. As the interest in cell and tissue mechanics increase, agent-based models are becoming more common the modeling community. We overview the physical aspects, complexity, shortcomings, and capabilities of the major agent-based model categories: lattice-based models (cellular automata, lattice gas cellular automata, cellular Potts models), off-lattice models (center-based models, deformable cell models, vertex models), and hybrid discrete-continuum models. In this way, we hope to assist future researchers in choosing a model for the phenomenon they want to model and understand. The article also contains some novel results.

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“…Here, we introduce specific choices for the force terms to represent both the mechanical properties of the actomyosin cortex of a cell and the protein-protein interactions between neighboring cells. We represent both these mechanical interactions by linear springs, following previous IB method implementations [5,33,34,35,40], although different functional forms could, in principle, be chosen.…”

Section: Discretization Of Immersed Boundariesmentioning

confidence: 99%

“…Rejniak and Dillon employ a similar framework to explain the variety of different architectural forms in intraductal tumors [32]. Dillon and Othmer use an IB method to model spatial patterning of the vertebrate limb bud [5], and an IB framework for tackling general morphogenetic problems is presented by Tanaka, Sichau, and Iber [40]. Cell deformation is investigated by several authors; by Bottino in the context of passive actin cytoskeletal networks [1], by Jadhav, Eggleton, and Konstantopoulos with a three-dimensional implementation in the context of cell rolling [18], and by Le et al, who use a three-dimensional framework to investigate the deformation of red blood cells [19].…”

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confidence: 99%

Numerical Analysis of the Immersed Boundary Method for Cell-Based Simulation

Cooper¹,

Baker²,

Fletcher³

2017

SIAM J. Sci. Comput.

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Abstract. Mathematical modelling provides a useful framework within which to investigate the organization of biological tissues. With advances in experimental biology leading to increasingly detailed descriptions of cellular behavior, models that consider cells as individual objects are becoming a common tool to study how processes at the single-cell level affect collective dynamics and determine tissue size, shape, and function. However, there often remains no comprehensive account of these models, their method of solution, computational implementation, or analysis of parameter scaling, hindering our ability to utilize and accurately compare different models. Here we present an efficient, open-source implementation of the immersed boundary (IB) method, tailored to simulate the dynamics of cell populations. This approach considers the dynamics of elastic membranes, representing cell boundaries, immersed in a viscous Newtonian fluid. The IB method enables complex and emergent cell shape dynamics, spatially heterogeneous cell properties, and precise control of growth mechanisms. We solve the model numerically using an established algorithm, based on the fast Fourier transform, providing full details of all technical aspects of our implementation. The implementation is undertaken within Chaste, an open-source C++ library that allows one to easily change constitutive assumptions. Our implementation scales linearly with time step, and subquadratically with mesh spacing and immersed boundary node spacing. We identify the relationship between the immersed boundary node spacing and fluid mesh spacing required to ensure fluid volume conservation within immersed boundaries, and the scaling of cell membrane stiffness and cell-cell interaction strength required when refining the immersed boundary discretization. Finally, we present a simulation study of a growing epithelial tissue to demonstrate the applicability of our implementation to relevant biological questions, highlighting several features of the IB method that make it well suited to address certain questions in epithelial morphogenesis.

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LBIBCell: a cell-based simulation environment for morphogenetic problems

Abstract: The documentation and source code are available on http://tanakas.bitbucket.org/lbibcell/index.html

Cited by 59 publications

References 40 publications

A cell-based computational model of early embryogenesis coupling mechanical behaviour and gene regulation

A cell-based computational model of early embryogenesis coupling mechanical behaviour and gene regulation

Simulating tissue mechanics with agent-based models: concepts, perspectives and some novel results

Numerical Analysis of the Immersed Boundary Method for Cell-Based Simulation

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