Using multi-level Petri nets models to simulate microbiota resistance to antibiotics

Bardini, Roberta; Politano, Gianfranco; Benso, Alfredo; Carlo, Stefano Di

doi:10.1109/bibm.2017.8217637

Cited by 8 publications

(9 citation statements)

References 14 publications

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“…1) Compilation of NWNs models: NWNs extend the Petri Nets (PNs) formalism to support hierarchy, encapsulation, and selective communication [27], [24], [9], which makes them suitable to model complex biological processes [25], [28], coherently with the design goals of BiSDL (Section III-A). PNs are bipartite graphs where nodes The NWNs formalism is a high-level PNs formalism supporting all features of other high-level PNs: tokens of different types and timed and stochastic time delays associated with transitions.…”

Section: From Bisdl Descriptions To Nwns Modelsmentioning

confidence: 99%

Biology System Description Language (BiSDL): a modeling language for the design of multicellular synthetic biological systems

Giannantoni,

Bardini,

Savino

et al. 2024

Preprint

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Background: The Biology System Description Language (BiSDL) is an accessible, easy-to-use computational language for multicellular synthetic biology. It allows synthetic biologists to represent spatiality and multi-level cellular dynamics inherent to multicellular designs, filling a gap in the state of the art. Developed for designing and simulating spatial, multicellular synthetic biological systems, BiSDL integrates high-level conceptual design with detailed low-level modeling, fostering collaboration in the Design-Build-Test-Learn cycle. BiSDL descriptions directly compile into Nets-Within-Nets (NWNs) models, offering a unique approach to spatial and hierarchical modeling in biological systems. Results: BiSDL's effectiveness is showcased through two case studies on complex multicellular systems: a bacterial consortium and a synthetic morphogen system. These studies highlight the BiSDL proficiency in representing spatial interactions and multi-level cellular dynamics. The language facilitates the compilation of conceptual designs into detailed, simulatable models, leveraging the NWNs formalism. This enables intuitive modeling of complex biological systems, making advanced computational tools more accessible to a broader range of researchers. Conclusions: BiSDL represents a significant step forward in computational languages for synthetic biology, providing a sophisticated yet user-friendly tool for the design and simulation of complex biological systems with an emphasis on spatiality and cellular dynamics. Its introduction has the potential to transform research and development in synthetic biology, allowing for deeper insights and novel applications in understanding and manipulating multicellular systems.

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Section: From Bisdl Descriptions To Nwns Modelsmentioning

confidence: 99%

Biology System Description Language (BiSDL): a modeling language for the design of multicellular synthetic biological systems

Giannantoni,

Bardini,

Savino

et al. 2024

Preprint

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“…yet are less frequent, also due to their lack of standardization [30]. High-level Petri Nets (PN) models are accessible, formally complete, and naturally support modeling of complex biological processes [31] such as ontogenesis [32,33] or the relations between a host organism and the microbiota [34,35]. Other approaches, such as vertex models [36],…”

Section: Models Of Biological Complexitymentioning

confidence: 99%

A methodology combining reinforcement learning and simulation to optimize thein silicoculture of epithelial sheets

Castrignanò

Bardini

Savino

et al. 2023

Preprint

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Tissue Engineering and Regenerative Medicine aim to replicate and replace tissues for curing disease. However, full tissue integration and homeostasis are still far from reach. Biofabrication is an emerging field that identifies the processes required for generating biologically functional products with the desired structural organization and functionality and can potentially revolutionize the regenerative medicine domain, which aims to use patients' cells to restore the structure and function of damaged tissues and organs. However, biofabrication still has limitations in the quality of processes and products. Biofabrication processes are often improved empirically, but this is slow, costly, and provides partial results. Computational approaches can tap into biofabrication underused potential, supporting analysis, modeling, design, and optimization of biofabrication processes, speeding up their improvement towards a higher quality of products and subsequent higher clinical relevance. This work proposes a reinforcement learning-based computational design space exploration methodology to generate optimal protocols for the simulated fabrication of epithelial sheets. The optimization strategy relies on a deep reinforcement learning algorithm, the Advantage-Actor Critic, which relies on a neural network model for learning. In contrast, simulations rely on the PalaCell2D simulation framework. Validation demonstrates the proposed approach on two protocol generation targets: maximizing the final number of obtained cells and optimizing the spatial organization of the cell aggregate.Advantage-Actor Critic, which relies on a neural network model for learning. In contrast, simulations rely on the PalaCell2D simulation framework. Validation demonstrates the proposed approach on two protocol generation targets: maximizing the final number of obtained cells and optimizing the spatial organization of the cell aggregate.

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“…The idea of tokens being PN goes back to R. Valk [71] , and NWN approaches are extensively studied in the PN literature [40] , [46] , [63] , [10] . The Nets-Within-Nets (NWN) formalism supports all capabilities of other high-level PN and can face the additional modeling requirements posed by ontogenetic processes [5] , [3] as will be explained in the next sections. Among the different flavors of the NWN formalisms, this paper adopts the one provided by the Renew simulator [41] , [11] , [70] .…”

Section: Introductionmentioning

confidence: 99%

Nets-within-nets for modeling emergent patterns in ontogenetic processes

Bardini

Benso

Politano

et al. 2021

Computational and Structural Biotechnology Journal

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Using multi-level Petri nets models to simulate microbiota resistance to antibiotics

Cited by 8 publications

References 14 publications

Biology System Description Language (BiSDL): a modeling language for the design of multicellular synthetic biological systems

Biology System Description Language (BiSDL): a modeling language for the design of multicellular synthetic biological systems

A methodology combining reinforcement learning and simulation to optimize thein silicoculture of epithelial sheets

Nets-within-nets for modeling emergent patterns in ontogenetic processes

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