PolyMorph: Extension of PolyHoop for tissue morphogenesis coupled to chemical signaling

IF 7.2 2区 物理与天体物理 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Nicolas Pascal Guido Müller , Roman Vetter
{"title":"PolyMorph: Extension of PolyHoop for tissue morphogenesis coupled to chemical signaling","authors":"Nicolas Pascal Guido Müller ,&nbsp;Roman Vetter","doi":"10.1016/j.cpc.2025.109581","DOIUrl":null,"url":null,"abstract":"<div><div>We present PolyMorph, a lightweight standalone C++ program that extends its predecessor PolyHoop by a finite-difference solver for multi-component reaction-advection-diffusion equations. PolyMorph simulates two integral parts of tissue morphogenesis in two dimensions: 1) the mechanics of cellular deformation, growth and proliferation, and 2) transport and reaction of an arbitrary number of chemical species. Both of these components are bidirectionally coupled, allowing cells to base their behavior on local information on concentrations and flow, and allowing the chemical transport and reaction kinetics to depend on spatial information such as the local cell type. This bidirectional feedback makes PolyMorph a versatile tool to study a variety of cellular morphogenetic processes such as chemotaxis, cell sorting, tissue patterning with morphogen gradients, Turing patterning, and diffusion- or supply-limited growth with sub-cellular resolution.</div></div><div><h3>Program summary</h3><div><em>Program Title:</em> PolyMorph</div><div><em>CPC Library link to program files:</em> <span><span>https://doi.org/10.17632/4jscxhkd2s.2</span><svg><path></path></svg></span></div><div><em>Licensing provisions:</em> BSD 3-clause</div><div><em>Programming language:</em> C++11</div><div><em>Supplementary material:</em> Figure 1</div><div><em>Journal reference of previous version:</em> Comput. Phys. Commun. 299 (2024) 109128, <span><span>https://doi.org/10.1016/j.cpc.2024.109128</span><svg><path></path></svg></span></div><div><em>Does the new version supersede the previous version?:</em> No</div><div><em>Nature of problem:</em> In tissue development and disease, morphogenesis and cell fate determination depends on mechanical processes as well as chemical signaling. PolyMorph couples the Newtonian mechanics of deformable cells (including growth and proliferation) in 2D with a customizable set of reaction-advection-diffusion equations to simulate problems that require an integrated approach with chemical-mechanical interactions. Typical use cases include the patterning of epithelial tissues with chemical signals (e.g., morphogen gradients or the Turing mechanism), chemotaxis and cell migration, wound healing, diffusion- or nutrition-limited growth, regulatory network dynamics in a spatial cellular environment, and other problems in tissue self-organization. PolyMorph enables the numerical solution of such problems with bidirectional feedback between mechanics and chemistry, in large monolayer tissues and with an arbitrary number of interacting species.</div><div><em>Solution method:</em> The off-lattice polygonal representation of cell boundaries in PolyHoop [1] is coupled to a lattice representation of diffusing chemical reactants. The reaction-advection-diffusion problem is solved with the finite difference method using the standard 5-point central difference stencil, and explicitly integrated in time. A scatter-gather approach inspired by the particle-in-cell method interpolates between the Lagrangian cell boundaries and the Eulerian finite-difference grid. The program is parallelized with OpenMP and does not use any external libraries.</div><div><em>Reasons for the new version:</em> The original program PolyHoop solves the Newtonian mechanics of deformable particles, foams and cellular tissues in two dimensions. In the application realm of developmental and systems biology, however, various morphogenetic problems depend not only on cell mechanics, but also on chemical signaling, nutrient supply etc. The solution of such external transport problems was not part of PolyHoop, but is available in some related codes [2–5]. We have extended PolyHoop to create a new program named PolyMorph, introduced here. It enables the simulation of cellular tissue dynamics with bidirectional coupling to a multi-component diffusion system, which substantially widens the potential scope of application.</div><div><em>Summary of revisions:</em> PolyMorph introduces a solver for <em>n</em> coupled reaction-advection-diffusion equations for concentrations <span><math><msub><mrow><mi>c</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span>, of the form<span><span><span><math><mfrac><mrow><mo>∂</mo><msub><mrow><mi>c</mi></mrow><mrow><mi>i</mi></mrow></msub></mrow><mrow><mo>∂</mo><mi>t</mi></mrow></mfrac><mo>=</mo><msub><mrow><mi>D</mi></mrow><mrow><mi>i</mi></mrow></msub><mrow><mo>(</mo><mfrac><mrow><msup><mrow><mo>∂</mo></mrow><mrow><mn>2</mn></mrow></msup></mrow><mrow><mo>∂</mo><msup><mrow><mi>x</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></mfrac><mo>+</mo><msub><mrow><mi>α</mi></mrow><mrow><mi>i</mi></mrow></msub><mfrac><mrow><msup><mrow><mo>∂</mo></mrow><mrow><mn>2</mn></mrow></msup></mrow><mrow><mo>∂</mo><msup><mrow><mi>y</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></mfrac><mo>)</mo></mrow><msub><mrow><mi>c</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>−</mo><mi>∇</mi><mo>⋅</mo><mo>(</mo><mover><mrow><mi>v</mi></mrow><mrow><mo>→</mo></mrow></mover><msub><mrow><mi>c</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>)</mo><mo>+</mo><msub><mrow><mi>R</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>(</mo><mi>p</mi><mo>,</mo><msub><mrow><mi>c</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><msub><mrow><mi>c</mi></mrow><mrow><mi>n</mi></mrow></msub><mo>,</mo><msub><mrow><mi>k</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><msub><mrow><mi>k</mi></mrow><mrow><mi>m</mi></mrow></msub><mo>,</mo><mi>t</mi><mo>)</mo><mo>.</mo></math></span></span></span> The reaction terms <span><math><msub><mrow><mi>R</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span> can be user-specified in the form of C++11 lambda functions, parameterized by the local polygon (cell) <em>p</em> and a set of <em>m</em> kinetic coefficients <span><math><msub><mrow><mi>k</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><msub><mrow><mi>k</mi></mrow><mrow><mi>m</mi></mrow></msub></math></span>. Both the kinetic coefficients <span><math><msub><mrow><mi>k</mi></mrow><mrow><mi>j</mi></mrow></msub><mo>(</mo><mi>x</mi><mo>,</mo><mi>y</mi><mo>)</mo></math></span> and the diffusivities <span><math><msub><mrow><mi>D</mi></mrow><mrow><mi>i</mi></mrow></msub><mo>(</mo><mi>x</mi><mo>,</mo><mi>y</mi><mo>)</mo></math></span> (the latter assumed to be piece-wise constant) can access tissue information such as the local cell type through a map <span><math><mo>(</mo><mi>x</mi><mo>,</mo><mi>y</mi><mo>)</mo><mo>→</mo><mi>p</mi></math></span>. This allows for cell-specific transport and reaction kinetics. At their birth, cells can draw their own random kinetic parameters to represent cell-to-cell variability [6,7]. In interstitial space or outside of the region occupied by the tissue, background coefficients can be specified. Note that the general form of <span><math><msub><mrow><mi>R</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span> also allows for 0<sup>th</sup>- or 1<sup>st</sup>-order reactions, such as morphogen production or degradation. The coefficients <span><math><msub><mrow><mi>α</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span> control the degree of anisotropy in the diffusion of each species.</div><div>To simulate advection and dilution in moving, deforming and growing tissues, a discretized velocity field <span><math><mover><mrow><mi>v</mi></mrow><mrow><mo>→</mo></mrow></mover><mo>(</mo><mi>x</mi><mo>,</mo><mi>y</mi><mo>)</mo></math></span> is interpolated on the finite-difference grid from the underlying off-lattice motion of cellular boundaries. Inside cells, inverse distance weighting (IDW) of the cell vertex velocities is used. In the extracellular space, three options are available (Supplementary Fig. 1): i) IDW within a user-defined cutoff radius, ii) bilinear interpolation or iii) zero velocity. At the lattice borders, Dirichlet and Neumann boundary conditions can be specified.</div><div>For the coupling in opposite direction, all relevant cellular model parameters of PolyHoop, such as cortical tension, growth rates, etc., can be made dependent on a local readout of species concentrations <span><math><msub><mrow><mi>c</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span> and their gradients <span><math><mi>∇</mi><msub><mrow><mi>c</mi></mrow><mrow><mi>i</mi></mrow></msub></math></span>, via user-specifiable C++11 lambda functions <span><math><mi>f</mi><mo>(</mo><mi>p</mi><mo>,</mo><msub><mrow><mi>c</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><msub><mrow><mi>c</mi></mrow><mrow><mi>n</mi></mrow></msub><mo>,</mo><mi>∇</mi><msub><mrow><mi>c</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>,</mo><mo>.</mo><mo>.</mo><mo>.</mo><mo>,</mo><mi>∇</mi><msub><mrow><mi>c</mi></mrow><mrow><mi>n</mi></mrow></msub><mo>,</mo><mi>t</mi><mo>)</mo></math></span>. Contact parameters (the adhesion strength and the friction coefficient) can be defined based on the properties of both cells involved in the contact, allowing to model differential adhesion for instance. In addition, a chemotactic force vector and a cell type specifier can be defined in the above functional form.</div><div><em>Additional comments including restrictions and unusual features:</em> PolyMorph inherits all physical features of its predecessor PolyHoop except cell fusion, but relaxes its design paradigm of strictly minimal code somewhat, in favor of more modularity to account for the increased level of complexity. It does therefore not supersede PolyHoop, but rather represents a spin-off program. The name PolyMorph conveys the shifted focus on morphogenetic problems involving a coupling to multi-component species transport.</div><div>Like PolyHoop, PolyMorph writes a series of VTK output files that can be viewed in ParaView. A structured grid file (.vts) containing user-specified lattice data is written for every animation frame. The user may further call the function <span>Ensemble::write_OFF()</span> to save a tissue in its current state in the common Object File Format (.off), for later use as a starting point of a different simulation.</div><div>Three limitations of the current implementation are that only diagonal elements in the diffusion coefficient matrix are supported, both the cell mechanics and the finite-difference solver operate with the same timestep, and both spatial directions use the same grid spacing.</div></div><div><h3>References</h3><div><ul><li><span>[1]</span><span><div>R. Vetter, V. Runser, D. Iber, PolyHoop: soft particle and tissue dynamics with topological transitions, Comput. Phys. Commun. 299 (2024) 109128</div></span></li><li><span>[2]</span><span><div>K.A. Rejniak, A single-cell approach in modeling the dynamics of tumor microregions, Math. Biosci. Eng. 2 (2005) 643–655</div></span></li><li><span>[3]</span><span><div>S. Tanaka, D. Sichau, D. Iber, LBIBCell: a cell-based simulation environment for morphogenetic problems, Bioinformatics 31 (2015) 2340–2347</div></span></li><li><span>[4]</span><span><div>B. Merchant, L. Edelstein-Keshet, J.J. Feng, A Rho-GTPase based model explains spontaneous collective migration of neural crest cell clusters, Dev. Biol. 444(Suppl. 1) (2018) S262–S273</div></span></li><li><span>[5]</span><span><div>R. Conradin, C. Coreixas, J. Latt, B. Chopard, PalaCell2D: a framework for detailed tissue morphogenesis, J. Comput. Sci. 53 (2021) 101353</div></span></li><li><span>[6]</span><span><div>R. Vetter, D. Iber, Precision of morphogen gradients in neural tube development. Nat. Commun. 13 (2022) 1145</div></span></li><li><span>[7]</span><span><div>Y. Long, R. Vetter, D. Iber, 2D effects enhance precision of gradient-based tissue patterning, iScience 26 (2023) 107880</div></span></li></ul></div></div>","PeriodicalId":285,"journal":{"name":"Computer Physics Communications","volume":"312 ","pages":"Article 109581"},"PeriodicalIF":7.2000,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Physics Communications","FirstCategoryId":"101","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010465525000840","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

We present PolyMorph, a lightweight standalone C++ program that extends its predecessor PolyHoop by a finite-difference solver for multi-component reaction-advection-diffusion equations. PolyMorph simulates two integral parts of tissue morphogenesis in two dimensions: 1) the mechanics of cellular deformation, growth and proliferation, and 2) transport and reaction of an arbitrary number of chemical species. Both of these components are bidirectionally coupled, allowing cells to base their behavior on local information on concentrations and flow, and allowing the chemical transport and reaction kinetics to depend on spatial information such as the local cell type. This bidirectional feedback makes PolyMorph a versatile tool to study a variety of cellular morphogenetic processes such as chemotaxis, cell sorting, tissue patterning with morphogen gradients, Turing patterning, and diffusion- or supply-limited growth with sub-cellular resolution.

Program summary

Program Title: PolyMorph
CPC Library link to program files: https://doi.org/10.17632/4jscxhkd2s.2
Licensing provisions: BSD 3-clause
Programming language: C++11
Supplementary material: Figure 1
Journal reference of previous version: Comput. Phys. Commun. 299 (2024) 109128, https://doi.org/10.1016/j.cpc.2024.109128
Does the new version supersede the previous version?: No
Nature of problem: In tissue development and disease, morphogenesis and cell fate determination depends on mechanical processes as well as chemical signaling. PolyMorph couples the Newtonian mechanics of deformable cells (including growth and proliferation) in 2D with a customizable set of reaction-advection-diffusion equations to simulate problems that require an integrated approach with chemical-mechanical interactions. Typical use cases include the patterning of epithelial tissues with chemical signals (e.g., morphogen gradients or the Turing mechanism), chemotaxis and cell migration, wound healing, diffusion- or nutrition-limited growth, regulatory network dynamics in a spatial cellular environment, and other problems in tissue self-organization. PolyMorph enables the numerical solution of such problems with bidirectional feedback between mechanics and chemistry, in large monolayer tissues and with an arbitrary number of interacting species.
Solution method: The off-lattice polygonal representation of cell boundaries in PolyHoop [1] is coupled to a lattice representation of diffusing chemical reactants. The reaction-advection-diffusion problem is solved with the finite difference method using the standard 5-point central difference stencil, and explicitly integrated in time. A scatter-gather approach inspired by the particle-in-cell method interpolates between the Lagrangian cell boundaries and the Eulerian finite-difference grid. The program is parallelized with OpenMP and does not use any external libraries.
Reasons for the new version: The original program PolyHoop solves the Newtonian mechanics of deformable particles, foams and cellular tissues in two dimensions. In the application realm of developmental and systems biology, however, various morphogenetic problems depend not only on cell mechanics, but also on chemical signaling, nutrient supply etc. The solution of such external transport problems was not part of PolyHoop, but is available in some related codes [2–5]. We have extended PolyHoop to create a new program named PolyMorph, introduced here. It enables the simulation of cellular tissue dynamics with bidirectional coupling to a multi-component diffusion system, which substantially widens the potential scope of application.
Summary of revisions: PolyMorph introduces a solver for n coupled reaction-advection-diffusion equations for concentrations ci, of the formcit=Di(2x2+αi2y2)ci(vci)+Ri(p,c1,...,cn,k1,...,km,t). The reaction terms Ri can be user-specified in the form of C++11 lambda functions, parameterized by the local polygon (cell) p and a set of m kinetic coefficients k1,...,km. Both the kinetic coefficients kj(x,y) and the diffusivities Di(x,y) (the latter assumed to be piece-wise constant) can access tissue information such as the local cell type through a map (x,y)p. This allows for cell-specific transport and reaction kinetics. At their birth, cells can draw their own random kinetic parameters to represent cell-to-cell variability [6,7]. In interstitial space or outside of the region occupied by the tissue, background coefficients can be specified. Note that the general form of Ri also allows for 0th- or 1st-order reactions, such as morphogen production or degradation. The coefficients αi control the degree of anisotropy in the diffusion of each species.
To simulate advection and dilution in moving, deforming and growing tissues, a discretized velocity field v(x,y) is interpolated on the finite-difference grid from the underlying off-lattice motion of cellular boundaries. Inside cells, inverse distance weighting (IDW) of the cell vertex velocities is used. In the extracellular space, three options are available (Supplementary Fig. 1): i) IDW within a user-defined cutoff radius, ii) bilinear interpolation or iii) zero velocity. At the lattice borders, Dirichlet and Neumann boundary conditions can be specified.
For the coupling in opposite direction, all relevant cellular model parameters of PolyHoop, such as cortical tension, growth rates, etc., can be made dependent on a local readout of species concentrations ci and their gradients ci, via user-specifiable C++11 lambda functions f(p,c1,...,cn,c1,...,cn,t). Contact parameters (the adhesion strength and the friction coefficient) can be defined based on the properties of both cells involved in the contact, allowing to model differential adhesion for instance. In addition, a chemotactic force vector and a cell type specifier can be defined in the above functional form.
Additional comments including restrictions and unusual features: PolyMorph inherits all physical features of its predecessor PolyHoop except cell fusion, but relaxes its design paradigm of strictly minimal code somewhat, in favor of more modularity to account for the increased level of complexity. It does therefore not supersede PolyHoop, but rather represents a spin-off program. The name PolyMorph conveys the shifted focus on morphogenetic problems involving a coupling to multi-component species transport.
Like PolyHoop, PolyMorph writes a series of VTK output files that can be viewed in ParaView. A structured grid file (.vts) containing user-specified lattice data is written for every animation frame. The user may further call the function Ensemble::write_OFF() to save a tissue in its current state in the common Object File Format (.off), for later use as a starting point of a different simulation.
Three limitations of the current implementation are that only diagonal elements in the diffusion coefficient matrix are supported, both the cell mechanics and the finite-difference solver operate with the same timestep, and both spatial directions use the same grid spacing.

References

  • [1]
    R. Vetter, V. Runser, D. Iber, PolyHoop: soft particle and tissue dynamics with topological transitions, Comput. Phys. Commun. 299 (2024) 109128
  • [2]
    K.A. Rejniak, A single-cell approach in modeling the dynamics of tumor microregions, Math. Biosci. Eng. 2 (2005) 643–655
  • [3]
    S. Tanaka, D. Sichau, D. Iber, LBIBCell: a cell-based simulation environment for morphogenetic problems, Bioinformatics 31 (2015) 2340–2347
  • [4]
    B. Merchant, L. Edelstein-Keshet, J.J. Feng, A Rho-GTPase based model explains spontaneous collective migration of neural crest cell clusters, Dev. Biol. 444(Suppl. 1) (2018) S262–S273
  • [5]
    R. Conradin, C. Coreixas, J. Latt, B. Chopard, PalaCell2D: a framework for detailed tissue morphogenesis, J. Comput. Sci. 53 (2021) 101353
  • [6]
    R. Vetter, D. Iber, Precision of morphogen gradients in neural tube development. Nat. Commun. 13 (2022) 1145
  • [7]
    Y. Long, R. Vetter, D. Iber, 2D effects enhance precision of gradient-based tissue patterning, iScience 26 (2023) 107880
PolyMorph:组织形态发生与化学信号耦合的PolyHoop的延伸
我们介绍了PolyMorph,一个轻量级的独立c++程序,它通过多组分反应-平流-扩散方程的有限差分求解器扩展了其前身PolyHoop。PolyMorph在两个维度上模拟了组织形态发生的两个组成部分:1)细胞变形、生长和增殖的机制,以及2)任意数量的化学物质的运输和反应。这两种成分都是双向耦合的,允许细胞根据浓度和流量的局部信息来决定它们的行为,并允许化学运输和反应动力学依赖于局部细胞类型等空间信息。这种双向反馈使得PolyMorph成为研究各种细胞形态发生过程的通用工具,如趋化性、细胞分选、具有形态梯度的组织图图化、图灵图图化以及具有亚细胞分辨率的扩散或供应限制生长。程序摘要程序标题:多态cpc库链接到程序文件:https://doi.org/10.17632/4jscxhkd2s.2Licensing条款:BSD 3-clause程序设计语言:c++ 11补充材料:图1上一版本的期刊参考:Comput。理论物理。common . 299 (2024) 109128, https://doi.org/10.1016/j.cpc.2024.109128Does新版本取代旧版本?问题的本质:在组织发育和疾病中,形态发生和细胞命运的决定既取决于化学信号,也取决于机械过程。PolyMorph将二维可变形细胞(包括生长和增殖)的牛顿力学与一套可定制的反应-平流-扩散方程相结合,以模拟需要化学-机械相互作用综合方法的问题。典型的用例包括上皮组织的化学信号模式(例如,形态梯度或图灵机制),趋化性和细胞迁移,伤口愈合,扩散或营养受限的生长,空间细胞环境中的调节网络动力学,以及组织自组织中的其他问题。PolyMorph能够在大型单层组织和任意数量的相互作用物种中实现力学和化学之间双向反馈的此类问题的数值解决。求解方法:PolyHoop[1]中细胞边界的非晶格多边形表示与扩散化学反应物的晶格表示相耦合。反应-平流-扩散问题采用标准5点中心差分模板,用有限差分法求解,并在时间上显式积分。在拉格朗日细胞边界和欧拉有限差分网格之间采用了一种受细胞内粒子方法启发的散射-收集方法。该程序与OpenMP并行,不使用任何外部库。新版本的原因:原来的程序PolyHoop解决了二维的可变形粒子、泡沫和细胞组织的牛顿力学。然而,在发育生物学和系统生物学的应用领域,各种形态发生问题不仅依赖于细胞力学,还与化学信号、营养供应等有关。这种外部传输问题的解决方案不是PolyHoop的一部分,但在一些相关规范中可以找到[2-5]。我们已经扩展了PolyHoop,创建了一个名为PolyMorph的新程序,在这里介绍。它能够模拟细胞组织动力学与多组分扩散系统的双向耦合,这大大拓宽了潜在的应用范围。修订总结:PolyMorph引入了一个求解n个浓度为ci的耦合反应-平流-扩散方程的求解器,其形式为∂ci∂t=Di(∂2∂x2+αi∂2∂y2)ci−∇⋅(v→ci)+Ri(p,c1,…,cn,k1,…,km,t)。反应项Ri可以用户以c++ 11 lambda函数的形式指定,由局部多边形(单元)p和一组m个动力学系数k1,…,km参数化。动力学系数kj(x,y)和扩散系数Di(x,y)(后者假定为切片常数)都可以通过映射(x,y)→p访问组织信息,例如局部细胞类型。这允许细胞特异性运输和反应动力学。在细胞诞生时,细胞可以绘制自己的随机动力学参数来表示细胞间的可变性[6,7]。在间隙空间或被组织占据的区域之外,可以指定背景系数。注意,Ri的一般形式也允许进行0级或1级反应,例如形态素的产生或降解。系数αi控制着各物种扩散的各向异性程度。为了模拟运动、变形和生长组织中的平流和稀释,从细胞边界的基本离格运动中插值到有限差分网格上的离散速度场v→(x,y)。在单元内部,使用单元顶点速度的逆距离加权(IDW)。 在胞外空间,有三种选择可用(补充图1):i)在用户定义的截止半径内的IDW, ii)双线性插值或iii)零速度。在点阵边界处,可以指定Dirichlet和Neumann边界条件。对于相反方向的耦合,PolyHoop的所有相关细胞模型参数,如皮质张力、生长速率等,都可以通过用户指定的c++ 11 lambda函数f(p,c1,…,cn,∇c1,…,cn, t)来依赖于物种浓度ci及其梯度∇ci的局部读出。接触参数(粘附强度和摩擦系数)可以根据接触中涉及的两个细胞的特性来定义,例如,允许建模不同的粘附。此外,趋化力矢量和细胞类型指示符可以用上述函数形式定义。附加说明,包括限制和不寻常的功能:PolyMorph继承了其前身PolyHoop的所有物理功能,除了细胞融合,但放松了其严格最小化代码的设计范式,以支持更多的模块化,以考虑复杂性的增加。因此,它不会取代PolyHoop,而是代表一个衍生程序。PolyMorph的名称传达了对涉及多组分物种运输耦合的形态发生问题的转移。像PolyHoop一样,PolyMorph编写了一系列可以在ParaView中查看的VTK输出文件。为每个动画帧编写包含用户指定的网格数据的结构化网格文件(.vts)。用户可以进一步调用函数Ensemble::write_OFF()以通用对象文件格式(.off)保存当前状态的组织,以供以后用作不同模拟的起点。当前实现的三个限制是:仅支持扩散系数矩阵中的对角元素,单元力学和有限差分求解器使用相同的时间步长,两个空间方向使用相同的网格间距。韦特,李泽文,李柏文,PolyHoop:基于拓扑跃迁的软粒子和组织动力学,计算机学报。理论物理。科学通报。299 (2024)109128[2]K.A.肿瘤微区动力学建模的单细胞方法,数学。Biosci。工程2 (2005)643-655 [3]S。田中军,李建军,李建军,李建军。基于细胞的细胞形态发育问题模拟研究,生物工程学报,2015,33(2):447 - 447。冯俊杰,冯俊杰,冯俊杰,基于Rho-GTPase的神经嵴细胞群自发集体迁移模型的研究,生物工程学报,444(增刊)。1) (2018) s262-s273;Conradin, C. Coreixas, J. Latt, B. Chopard, PalaCell2D:一个详细的组织形态发生框架,J. Comput。自然科学学报,53 (2021):10135135[6]R。张晓明,《神经管发育中形态梯度的准确性》。Nat common . 13 (2022) 1145[7]Y。张建军,张建军,张建军。基于梯度的组织图像提取方法研究,中国生物医学工程学报,34 (2):448 - 448
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来源期刊
Computer Physics Communications
Computer Physics Communications 物理-计算机:跨学科应用
CiteScore
12.10
自引率
3.20%
发文量
287
审稿时长
5.3 months
期刊介绍: The focus of CPC is on contemporary computational methods and techniques and their implementation, the effectiveness of which will normally be evidenced by the author(s) within the context of a substantive problem in physics. Within this setting CPC publishes two types of paper. Computer Programs in Physics (CPiP) These papers describe significant computer programs to be archived in the CPC Program Library which is held in the Mendeley Data repository. The submitted software must be covered by an approved open source licence. Papers and associated computer programs that address a problem of contemporary interest in physics that cannot be solved by current software are particularly encouraged. Computational Physics Papers (CP) These are research papers in, but are not limited to, the following themes across computational physics and related disciplines. mathematical and numerical methods and algorithms; computational models including those associated with the design, control and analysis of experiments; and algebraic computation. Each will normally include software implementation and performance details. The software implementation should, ideally, be available via GitHub, Zenodo or an institutional repository.In addition, research papers on the impact of advanced computer architecture and special purpose computers on computing in the physical sciences and software topics related to, and of importance in, the physical sciences may be considered.
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