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启动与停止:一款用于交互式模拟控制的PhysiCell和PhysiBoSS 2.0插件。

Start & Stop: a PhysiCell and PhysiBoSS 2.0 add-on for interactive simulation control.

作者信息

Smeriglio Riccardo, Bardini Roberta, Savino Alessandro, Di Carlo Stefano

机构信息

Department of Control and Computer Engineering, Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129, Turin, TO, Italy.

出版信息

BMC Bioinformatics. 2025 Jun 11;26(1):158. doi: 10.1186/s12859-025-06144-x.

DOI:10.1186/s12859-025-06144-x
PMID:40500690
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12160357/
Abstract

In computational biology, in silico simulators are vital for exploring and understanding the behavior of complex biological systems. Hybrid multi-level simulators, such as PhysiCell and PhysiBoSS 2.0, integrate multiple layers of biological complexity, providing deeper insights into emergent patterns. However, one key limitation of these simulators is the inability to adjust simulation parameters once the simulation has started, which hinders the interactive exploration and adaptation of dynamic protocols ranging from biofabrication to in vitro pharmacological testing. To address this challenge, we introduce the Start & Stop add-on for PhysiCell and PhysiBoSS 2.0. This add-on offers multi-level state preservation and multi-modal stop control, triggered by simulation time or cell conditions, enabling users to pause a simulation, adjust parameters, and then resume from the exact halted state. We validate Start & Stop using two well-established PhysiBoSS 2.0 use cases, a tumor spheroid 3T3 mouse fibroblasts use case under tumor necrosis factor (TNF) stimulation, and a lung cancer cell line invasion simulation, demonstrating that it preserves the simulator's original behavior while enabling interactive configuration changes that facilitate the exploration of diverse and adaptive treatment strategies. By enhancing flexibility and user interaction, Start & Stop makes PhysiCell and PhysiBoSS 2.0 more akin to real in vitro scenarios, thus expanding the range of potential simulations and advancing more effective protocol development in a variety of applications.

摘要

在计算生物学中,计算机模拟对于探索和理解复杂生物系统的行为至关重要。混合多层次模拟器,如PhysiCell和PhysiBoSS 2.0,整合了生物复杂性的多个层面,能更深入地洞察涌现模式。然而,这些模拟器的一个关键限制是,一旦模拟开始就无法调整模拟参数,这阻碍了从生物制造到体外药理学测试等动态协议的交互式探索和调整。为应对这一挑战,我们为PhysiCell和PhysiBoSS 2.0引入了“启动与停止”插件。该插件提供多层次状态保存和多模式停止控制,由模拟时间或细胞条件触发,使用户能够暂停模拟、调整参数,然后从精确的暂停状态恢复。我们使用两个成熟的PhysiBoSS 2.0用例验证了“启动与停止”功能,一个是肿瘤坏死因子(TNF)刺激下的肿瘤球状体3T3小鼠成纤维细胞用例,另一个是肺癌细胞系侵袭模拟,证明它在保持模拟器原始行为的同时,允许进行交互式配置更改,有助于探索多样的适应性治疗策略。通过增强灵活性和用户交互性,“启动与停止”功能使PhysiCell和PhysiBoSS 2.0更接近真实的体外场景,从而扩大了潜在模拟的范围,并在各种应用中推进更有效的协议开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/a3bc55507256/12859_2025_6144_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/f6ca8d206d15/12859_2025_6144_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/1a32cfc92210/12859_2025_6144_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/0983109121cd/12859_2025_6144_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/b55744fbaea1/12859_2025_6144_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/feb08c63e496/12859_2025_6144_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/a1267646b96f/12859_2025_6144_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/033c44b3c7a7/12859_2025_6144_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/a3bc55507256/12859_2025_6144_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/f6ca8d206d15/12859_2025_6144_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/1a32cfc92210/12859_2025_6144_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/0983109121cd/12859_2025_6144_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/b55744fbaea1/12859_2025_6144_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/feb08c63e496/12859_2025_6144_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/a1267646b96f/12859_2025_6144_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/033c44b3c7a7/12859_2025_6144_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd1f/12160357/a3bc55507256/12859_2025_6144_Fig8_HTML.jpg

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本文引用的文献

1
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Comput Struct Biotechnol J. 2024 Jan 2;23:601-616. doi: 10.1016/j.csbj.2023.12.035. eCollection 2024 Dec.
2
PhysiBoSS 2.0: a sustainable integration of stochastic Boolean and agent-based modelling frameworks.PhysiBoSS 2.0:随机布尔和基于主体建模框架的可持续集成。
NPJ Syst Biol Appl. 2023 Oct 30;9(1):54. doi: 10.1038/s41540-023-00314-4.
3
Multiscale model of the different modes of cancer cell invasion.
多尺度模型研究癌细胞的不同侵袭模式。
Bioinformatics. 2023 Jun 1;39(6). doi: 10.1093/bioinformatics/btad374.
4
Nets-within-nets for modeling emergent patterns in ontogenetic processes.用于模拟个体发育过程中涌现模式的网中网模型。
Comput Struct Biotechnol J. 2021 Oct 9;19:5701-5721. doi: 10.1016/j.csbj.2021.10.008. eCollection 2021.
5
PhysiBoSS: a multi-scale agent-based modelling framework integrating physical dimension and cell signalling.PhysiBoSS:一个整合物理维度和细胞信号的多尺度基于代理的建模框架。
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6
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PLoS Comput Biol. 2018 Feb 23;14(2):e1005991. doi: 10.1371/journal.pcbi.1005991. eCollection 2018 Feb.
7
MaBoSS 2.0: an environment for stochastic Boolean modeling.MaBoSS 2.0:用于随机布尔建模的环境。
Bioinformatics. 2017 Jul 15;33(14):2226-2228. doi: 10.1093/bioinformatics/btx123.
8
Multi-level and hybrid modelling approaches for systems biology.用于系统生物学的多层次和混合建模方法。
Comput Struct Biotechnol J. 2017 Aug 10;15:396-402. doi: 10.1016/j.csbj.2017.07.005. eCollection 2017.
9
Mathematical and Computational Modeling in Complex Biological Systems.复杂生物系统中的数学与计算建模
Biomed Res Int. 2017;2017:5958321. doi: 10.1155/2017/5958321. Epub 2017 Mar 13.
10
NF-κB signalling and cell fate decisions in response to a short pulse of tumour necrosis factor.肿瘤坏死因子短脉冲刺激下 NF-κB 信号转导与细胞命运决定
Sci Rep. 2016 Dec 22;6:39519. doi: 10.1038/srep39519.