STEPS: efficient simulation of stochastic reaction-diffusion models in realistic morphologies
STEPS: efficient simulation of stochastic reaction-diffusion models in realistic morphologies
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DOI：
10.1186/1752-0509-6-36
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发表时间：
2012-05-10
影响因子：
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通讯作者：
De Schutter, Erik
中科院分区：
文献类型：
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作者：
Hepburn, Iain;Chen, Weiliang;De Schutter, Erik
背景资料：细胞分子系统的模型是由生化反应（包括配体和膜结合蛋白之间的相互作用），构象变化和主动和被动运输等组成部分建立的。一个离散的，随机的动力学描述往往是必不可少的准确捕捉系统的行为。当空间效应起重要作用时，细胞的复杂形态可能必须表现出来，沿着的还有化学定位和扩散等方面。这种高层次的细节使得效率的软件，旨在模拟这样的systems.Results的一个特别重要的考虑因素：我们描述的步骤，一个随机的反应扩散模拟器开发的重点是模拟生化信号通路准确和有效地。STEPS支持所有上述功能，并且对SBML的良好验证支持允许可靠地导入许多现有的生化模型。复杂的边界可以准确地表示在外部生成的三维四面体网格导入STEPS。强大的Python接口有助于模型构建和仿真控制。STEPS实现了合成和拒绝方法，这是吉莱斯皮SSA的一个变体，支持在高效的搜索和更新引擎中四面体元素之间的扩散。实现了对良好混合条件和确定性模型解决方案的额外支持。求解器的准确性得到证实，与原始的和广泛的验证集组成的孤立的反应，扩散和反应扩散系统。精确度对四面体尺寸施加了上限和下限，这将详细描述。通过与Smoldyn的比较，我们展示了STEPS中基于体素的方法通常比基于粒子的方法更快，在更大的系统中具有越来越大的优势，并通过与MesoRD的比较，我们展示了STEPS实现的效率。结论：STEPS在C/C++中模拟了具有复杂边界的细胞反应扩散系统模型，具有高精度和高性能，由功能强大且用户友好的Python界面控制。STEPS是免费使用的，可在http://steps.sourceforge.net/上获得
Background: Models of cellular molecular systems are built from components such as biochemical reactions (including interactions between ligands and membrane-bound proteins), conformational changes and active and passive transport. A discrete, stochastic description of the kinetics is often essential to capture the behavior of the system accurately. Where spatial effects play a prominent role the complex morphology of cells may have to be represented, along with aspects such as chemical localization and diffusion. This high level of detail makes efficiency a particularly important consideration for software that is designed to simulate such systems.Results: We describe STEPS, a stochastic reaction-diffusion simulator developed with an emphasis on simulating biochemical signaling pathways accurately and efficiently. STEPS supports all the above-mentioned features, and well-validated support for SBML allows many existing biochemical models to be imported reliably. Complex boundaries can be represented accurately in externally generated 3D tetrahedral meshes imported by STEPS. The powerful Python interface facilitates model construction and simulation control. STEPS implements the composition and rejection method, a variation of the Gillespie SSA, supporting diffusion between tetrahedral elements within an efficient search and update engine. Additional support for well-mixed conditions and for deterministic model solution is implemented. Solver accuracy is confirmed with an original and extensive validation set consisting of isolated reaction, diffusion and reaction-diffusion systems. Accuracy imposes upper and lower limits on tetrahedron sizes, which are described in detail. By comparing to Smoldyn, we show how the voxel-based approach in STEPS is often faster than particle-based methods, with increasing advantage in larger systems, and by comparing to MesoRD we show the efficiency of the STEPS implementation.Conclusion: STEPS simulates models of cellular reaction-diffusion systems with complex boundaries with high accuracy and high performance in C/C++, controlled by a powerful and user-friendly Python interface. STEPS is free for use and is available at http://steps.sourceforge.net/