137 research outputs found

    Implementing vertex dynamics models of cell populations in biology within a consistent computational framework

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    The dynamic behaviour of epithelial cell sheets plays a central role during development, growth, disease and wound healing. These processes occur as a result of cell adhesion, migration, division, differentiation and death, and involve multiple processes acting at the cellular and molecular level. Computational models offer a useful means by which to investigate and test hypotheses about these processes, and have played a key role in the study of cell–cell interactions. However, the necessarily complex nature of such models means that it is difficult to make accurate comparison between different models, since it is often impossible to distinguish between differences in behaviour that are due to the underlying model assumptions, and those due to differences in the in silico implementation of the model. In this work, an approach is described for the implementation of vertex dynamics models, a discrete approach that represents each cell by a polygon (or polyhedron) whose vertices may move in response to forces. The implementation is undertaken in a consistent manner within a single open source computational framework, Chaste, which comprises fully tested, industrial-grade software that has been developed using an agile approach. This framework allows one to easily change assumptions regarding force generation and cell rearrangement processes within these models. The versatility and generality of this framework is illustrated using a number of biological examples. In each case we provide full details of all technical aspects of our model implementations, and in some cases provide extensions to make the models more generally applicable

    Taking aim at moving targets in computational cell migration

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    Cell migration is central to the development and maintenance of multicellular organisms. Fundamental understanding of cell migration can, for example, direct novel therapeutic strategies to control invasive tumor cells. However, the study of cell migration yields an overabundance of experimental data that require demanding processing and analysis for results extraction. Computational methods and tools have therefore become essential in the quantification and modeling of cell migration data. We review computational approaches for the key tasks in the quantification of in vitro cell migration: image pre-processing, motion estimation and feature extraction. Moreover, we summarize the current state-of-the-art for in silico modeling of cell migration. Finally, we provide a list of available software tools for cell migration to assist researchers in choosing the most appropriate solution for their needs

    Simulating tissue mechanics with Agent Based Models: concepts and perspectives

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    International audienceIn this paper we present an overview of agent based 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

    Development of a Three Dimensional Multiscale Computational Model of the Human Epidermis

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    Transforming Growth Factor (TGF-β1) is a member of the TGF-beta superfamily ligand-receptor network. and plays a crucial role in tissue regeneration. The extensive in vitro and in vivo experimental literature describing its actions nevertheless describe an apparent paradox in that during re-epithelialisation it acts as proliferation inhibitor for keratinocytes. The majority of biological models focus on certain aspects of TGF-β1 behaviour and no one model provides a comprehensive story of this regulatory factor's action. Accordingly our aim was to develop a computational model to act as a complementary approach to improve our understanding of TGF-β1. In our previous study, an agent-based model of keratinocyte colony formation in 2D culture was developed. In this study this model was extensively developed into a three dimensional multiscale model of the human epidermis which is comprised of three interacting and integrated layers: (1) an agent-based model which captures the biological rules governing the cells in the human epidermis at the cellular level and includes the rules for injury induced emergent behaviours, (2) a COmplex PAthway SImulator (COPASI) model which simulates the expression and signalling of TGF-β1 at the sub-cellular level and (3) a mechanical layer embodied by a numerical physical solver responsible for resolving the forces exerted between cells at the multi-cellular level. The integrated model was initially validated by using it to grow a piece of virtual epidermis in 3D and comparing the in virtuo simulations of keratinocyte behaviour and of TGF-β1 signalling with the extensive research literature describing this key regulatory protein. This research reinforces the idea that computational modelling can be an effective additional tool to aid our understanding of complex systems. In the accompanying paper the model is used to explore hypotheses of the functions of TGF-β1 at the cellular and subcellular level on different keratinocyte populations during epidermal wound healing

    Investigating biocomplexity through the agent-based paradigm.

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    Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines--or agents--to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex

    A review of mathematical models for the formation of vascular networks

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    Two major mechanisms are involved in the formation of blood vasculature: vasculogenesis and angiogenesis. The former term describes the formation of a capillary-like network from either a dispersed or a monolayered population of endothelial cells, reproducible also in vitro by specific experimental assays. The latter term describes the sprouting of new vessels from an existing capillary or post-capillary venule. Similar mechanisms are also involved in the formation of the lymphatic system through a process generally called lymphangiogenesis. A number of mathematical approaches have been used to analyse these phenomena. In this article, we review the different types of models, with special emphasis on their ability to reproduce different biological systems and to predict measurable quantities which describe the overall processes. Finally, we highlight the advantages specific to each of the different modelling approaches. The research that led to the present paper was partially supported by a grant of the group GNFM of INdA

    Simulation of the spatial structure and cellular organization evolution of cell aggregates arranged in various simple geometries, using a kinetic monte carlo method applied to a lattice model

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    ilustraciones, graficasEsta tesis trata los modelos de morfogénesis, en particular los modelos de evolución guiada por contacto que son coherentes con la hipótesis de la adhesión diferencial. Se presenta una revisión de algunos modelos, sus principios biológicos subyacentes, la relevancia y aplicaciones en el marco de la bioimpresión, la ingeniería de tejidos y la bioconvergencia. Luego, se presentan los detalles de los modelos basados en métodos de Monte Carlo para profundizar más adelante en el modelo basados en algoritmos Kinetic Monte Carlo (KMC) , más específicamente, se describe en detalle un modelo KMC de autoaprendizaje (SL-KMC). Se presenta y explica la estructura algorítmica del código implementado, se evalúa el rendimiento del modelo y se compara con un modelo KMC tradicional. Finalmente, se realizan los procesos de calibración y validación, se observó que el modelo es capaz de replicar la evolución del sistema multicelular cuando las condiciones de energía interfacial del sistema simulado son similares a las del sistema de calibraciones. (Texto tomado de la fuente)This thesis treats the models for morphogenesis, in particular the contact-guided evolution models that are coherent with the differential adhesion hypothesis. A review of some models, their biological underpinning principles, the relevance and applications in the framework of bioprinting, tissue engineering and bioconvergence are presented. Then the details for the Monte Carlo methods-based models are presented to later deep dive into the Kinetic Monte Carlo (KMC) based model, and more specifically a Self-Learning KMC (SL-KMC) model is described to detail. The algorithmic structure of the implemented code is presented and explained, the model performance is assessed and compared with a traditional KMC model. Finally, the calibration and validation processes have been carried out, it was observed that the model is able to replicate the multicellular system evolution when the interfacial energy conditions of the simulated system are similar to those of the calibrations system.MaestríaMagíster en Ingeniería - Ingeniería Químic

    多細胞組織のメゾスコピックレベルでの分解と再構成 : 複雑適応系の非平衡相転移理論に向けて

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    学位の種別: 課程博士審査委員会委員 : (主査)東京大学准教授 陳 昱, 東京大学教授 飛原 英治, 東京大学教授 奥田 洋司, 東京大学教授 大橋 弘忠, 京都大学准教授 井上 康博University of Tokyo(東京大学

    Bridging from single to collective cell migration: A review of models and links to experiments

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    Mathematical and computational models can assist in gaining an understanding of cell behavior at many levels of organization. Here, we review models in the literature that focus on eukaryotic cell motility at 3 size scales: intracellular signaling that regulates cell shape and movement, single cell motility, and collective cell behavior from a few cells to tissues. We survey recent literature to summarize distinct computational methods (phase-field, polygonal, Cellular Potts, and spherical cells). We discuss models that bridge between levels of organization, and describe levels of detail, both biochemical and geometric, included in the models. We also highlight links between models and experiments. We find that models that span the 3 levels are still in the minority.Comment: 39 pages, 5 figure
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