ya||a: GPU-powered Spheroid Models for Mesenchyme and Epithelium

Germann, Philipp; Marín-Riera, Miquel; Sharpe, James

doi:10.2139/ssrn.3188399

Cited by 8 publications

(12 citation statements)

References 45 publications

(10 reference statements)

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“…More generally, in several other systems, the skin physical forces exerted on/by cells by/on the extra-cellular environment (e.g., shear stress, compression, tension, traction, adhesion) have been linked to changes in extra-cellular matrix architecture, cell cycle, cell motility and signalling [ 61 , 62 , 63 , 64 , 65 , 66 ], likely playing a defining role in patterning processes. With the advent of biophysical tools to measure physical parameters in vivo [ 67 ] and the ever growing amount of theoretical frameworks integrating biomechanics [ 68 , 69 , 70 , 71 ], it now becomes possible to explore the role of tissue mechanics with comprehensive experimental modelling approaches. One may infer previous unified models by adding explicit dependence of some parameters of reaction-diffusion and chemotaxis terms on mechanical parameters (e.g., molecular diffusion could be a function of substrate stiffness [ 72 ]).…”

Section: Designing Numerical Evo-devo Approaches To Study Tissue Mmentioning

confidence: 99%

A “Numerical Evo-Devo” Synthesis for the Identification of Pattern-Forming Factors

Bailleul

Manceau

Touboul

2020

Cells

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Animals display extensive diversity in motifs adorning their coat, yet these patterns have reproducible orientation and periodicity within species or groups. Morphological variation has been traditionally used to dissect the genetic basis of evolutionary change, while pattern conservation and stability in both mathematical and organismal models has served to identify core developmental events. Two patterning theories, namely instruction and self-organisation, emerged from this work. Combined, they provide an appealing explanation for how natural patterns form and evolve, but in vivo factors underlying these mechanisms remain elusive. By bridging developmental biology and mathematics, novel frameworks recently allowed breakthroughs in our understanding of pattern establishment, unveiling how patterning strategies combine in space and time, or the importance of tissue morphogenesis in generating positional information. Adding results from surveys of natural variation to these empirical-modelling dialogues improves model inference, analysis, and in vivo testing. In this evo-devo-numerical synthesis, mathematical models have to reproduce not only given stable patterns but also the dynamics of their emergence, and the extent of inter-species variation in these dynamics through minimal parameter change. This integrative approach can help in disentangling molecular, cellular and mechanical interaction during pattern establishment.

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Section: Designing Numerical Evo-devo Approaches To Study Tissue Mmentioning

confidence: 99%

A “Numerical Evo-Devo” Synthesis for the Identification of Pattern-Forming Factors

Bailleul

Manceau

Touboul

2020

Cells

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“…To understand this, we turned to agent-based simulations of cellular aggregates using the GPU-based software ya||a (see Fig. 3A), which supports easy implementation of diverse cellular behaviours [43]. For simplicity, we considered a minimal model taking into account adherent and contractile protrusion interactions between cells.…”

Section: L(✓)mentioning

confidence: 99%

Arrested coalescence of multicellular aggregates

Oriola¹,

Marín-Riera²,

Anlaş³

et al. 2020

Preprint

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“…These models assume that cell trajectories in space can be assimilated to the motion of particles, which are governed by an equation of motion. CBMs have been used extensively to study the development of multiple organisms (Delile et al, 2017;Villoutreix et al, 2016;Germann et al, 2019;Van Liedekerke et al, 2018). We used a simplified mechanistic formulation of a CBM approach to simulate pectoral fin growth ( Fig.…”

Section: Computational Modelmentioning

confidence: 99%

Quantification of cell behaviours and computational modelling show that cell directional behaviours drive zebrafish pectoral fin morphogenesis

Dokmegang

Nguyen

Kardash

et al. 2020

Preprint

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Motivation: Understanding the mechanisms by which the zebrafish pectoral fin develops is expected to produce insights on how vertebrate limbs grow from a 2D cell layer to a 3D structure. Two mechanisms have been proposed to drive limb morphogenesis in tetrapods: a growth-based morphogenesis with a higher proliferation rate at the distal tip of the limb bud than at the proximal side, and directed cell behaviors that include elongation, division and migration in a nonrandom manner. Based on quantitative experimental biological data at the level of individual cells in the whole developing organ, we test the conditions for the dynamics of pectoral fin early morphogenesis. Results: We found that during the development of the zebrafish pectoral fin, cells have a preferential elongation axis that gradually aligns along the proximodistal axis (PD) of the organ. Based on these quantitative observations, we build a center-based cell model enhanced with a polarity term and cell proliferation to simulate fin growth. Our simulations resulted in 3D fins similar in shape to the observed ones, suggesting that the existence of a preferential axis of cell polarization is essential to drive fin morphogenesis in zebrafish, as observed in the development of limbs in the mouse, but distal tip-based expansion is not. Availability: Upon publication, biological data will be available at http://bioemergences.eu/modelingFin, and code source at https://github.com/guijoe/MaSoFin.

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ya||a: GPU-powered Spheroid Models for Mesenchyme and Epithelium

Cited by 8 publications

References 45 publications

A “Numerical Evo-Devo” Synthesis for the Identification of Pattern-Forming Factors

A “Numerical Evo-Devo” Synthesis for the Identification of Pattern-Forming Factors

Arrested coalescence of multicellular aggregates

Quantification of cell behaviours and computational modelling show that cell directional behaviours drive zebrafish pectoral fin morphogenesis

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