Modeling biological complexity using Biology System Description Language (BiSDL)

Muggianu, Flavia; Benso, Alfredo; Bardini, Roberta; Hu, Eric Y.; Politano, Gianfranco; Carlo, Stefano Di

doi:10.1109/bibm.2018.8621533

Cited by 6 publications

(7 citation statements)

References 9 publications

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“…The illustrated plasmidTransfer MODULE contains three SCOPE statements: one for the Donor cell (donor, (algorithm 5, lines 3-15); another one for the Transconjugant cell (transconjugant, algorithm 5, lines [21][22][23][24][25][26][27][28][29][30][31][32], and a third one for the Pilus proteinaceous structure mediating Fig. 12.…”

Section: Case Study 3 -Conjugative Plasmid Transfermentioning

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: Case Study 3 -Conjugative Plasmid Transfermentioning

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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“…Ordinary Differential Expressions (ODEs) usage is frequent in systems biology. In contrast, other approaches, such as Agent-Based Models (ABMs) and discrete models, have a great potential to enrich the toolkit of modelers in computational biology [28,29],…”

Section: Models Of Biological Complexitymentioning

confidence: 99%

“…Ordinary Differential Equations (ODEs) are common in systems biology [23], while Agent-Based Models (ABMs) and discrete models, though less standardized, offer significant potential in computational biology [24,25,26].…”

Section: Introductionmentioning

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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“…Finally, significant effort is required to improve the modeling strategy usability from life scientists with limited experience in model development and computer engineering. An effort in this direction is already in place with the development of the Biological System Description Language (BiSDL), a domain-specific high-level, modular programming language naturally accessible by purely biological semantics and automatically generating simulation-ready NWN models [49] .…”

Section: Conclusion and Future Perspectivesmentioning

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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Modeling biological complexity using Biology System Description Language (BiSDL)

Cited by 6 publications

References 9 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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