EpiLog: A software for the logical modelling of epithelial dynamics

Varela, Pedro L.; Ramos, Camila V.; Monteiro, Pedro T.; Chaouiya, Claudine

doi:10.12688/f1000research.15613.2

Cited by 12 publications

(13 citation statements)

References 23 publications

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“…Methods such as multiagent and lattice approaches are coming into wider use to represent evolving cell populations, cell migration, and deformation. Some researchers are experimenting with solutions using existing SBML packages (Watanabe & Myers, 2016;Varela et al, 2019). Modeling the development of tissues and organ function may also require combining these approaches with reaction-diffusion models, or multiphysics approaches (Nickerson et al, 2016).…”

Section: Layout and Renderingmentioning

confidence: 99%

SBMLLevel 3: an extensible format for the exchange and reuse of biological models

Keating¹,

Waltemath²,

König³

et al. 2020

Molecular Systems Biology

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240

202

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Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction‐based models and packages that extend the core with features suited to other model types including constraint‐based models, reaction‐diffusion models, logical network models, and rule‐based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single‐cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution.

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Section: Layout and Renderingmentioning

confidence: 99%

SBMLLevel 3: an extensible format for the exchange and reuse of biological models

Keating¹,

Waltemath²,

König³

et al. 2020

Molecular Systems Biology

Self Cite

240

202

View full text Add to dashboard Cite

show abstract

“…In the preceding section, we simulated the behaviour of cells for each of the three different presumptive territories by selecting appropriate combinations of signalling input levels, which were considered as fixed during the whole duration of the simulations. To model more precisely the production and diffusion of signalling molecules across the ectoderm, we used the software EpiLog (https://epilog-tool.org) (Varela et al, 2019) Table 2) (Fig. 8A).…”

Section: Multicellular Simulations Emphasise the Crucial Role Of Longmentioning

confidence: 99%

“…We took advantage of recent software Epilog (https://epilog-tool.org, v1.1.1.) (Varela et al, 2019) to perform multicellular simulations. Our epithelium model is nine cells wide and six cells long, made of hexagonal shaped cells, each one being in direct contact with at most six different neighbouring cells.…”

Section: Multicellular Simulation Using Epilogmentioning

confidence: 99%

Deciphering and modelling the TGF-β signalling interplays specifying the dorsal-ventral axis of the sea urchin embryo

Floc’hlay

Molina

Hernandez

et al. 2020

Preprint

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20 21 During sea urchin development, secretion of Nodal and BMP2/4 ligands and their antagonists 22 activation governs D/V patterning of the embryo. These results indicate that a mutual 34 antagonism between the Nodal and BMP2/4 pathways is the fundamental mechanism driving 35 early dorsal-ventral patterning. 36 37 Running title: Sea urchin DV axis specification 38 39 Key words: Paracentrotus lividus, embryo development, logical model, gene regulatory 40 network, Nodal pathway, BMP pathway. 41 42 Summary Statement: We propose a predictive computational model of the regulatory 43 network controlling the dorsal-ventral axis specification in sea urchin embryos, and highlight 44 key features of Nodal and BMP antagonism. 45 46

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“…Attempts to explicitly include regulatory networks into these agents [13] have shown that this can easily become computationally costly or would increase considerably the number of parameters to tune (e.g., PhysiBoSS [14]). Other applications rely on cellular automata, e.g., Epilog [15], or yet on the Potts model, which can be also considered as an agent-based approach [16]. Finally, some works (e.g., BooleanNet [17], or [18]) apply stochastic and probabilistic simulations but on non-interacting populations of cells.…”

Section: Introductionmentioning

confidence: 99%

UPMaBoSS: a novel framework for dynamic cell population modeling

Stoll

Naldi

Noël

et al. 2020

Preprint

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One of the aims of mathematical modeling is to understand and simulate the e↵ects of biological perturbations and suggest ways to intervene and reestablish proper cell functioning. However, it remains a challenge, especially when considering the dynamics at the level of a cell population, with cells dying, dividing and interacting. Here, we introduce a novel framework for the dynamical modelling of cell populations packaged into a dedicated tool, UPMaBoSS. We rely on the preexisting tool MaBoSS, which enables probabilistic simulations of cellular networks, and add a novel layer to account for cell interactions and population dynamics. We illustrate our methodology by means of a case study dealing with TNF-induced cell death. Interestingly, the simulation of cell population dynamics with UPMaBoSS reveals a mechanism of resistance triggered by TNF treatment. This appoach can be applied to diverse models of cellular networks, for example to study the impact of ligand release or drug treatments on cell fate decisions, such as commitment to proliferation, di↵erentiation, apoptosis, etc. Relatively easy to encode, UPMaBoSS simulations require only moderate computational power and execution time.To ease the reproduction of simulations, we provide several Jupyter notebooks that can be accessed within a new release of the CoLoMoTo Docker image, which contains all required software and the example models.

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EpiLog: A software for the logical modelling of epithelial dynamics

Cited by 12 publications

References 23 publications

SBMLLevel 3: an extensible format for the exchange and reuse of biological models

SBMLLevel 3: an extensible format for the exchange and reuse of biological models

Deciphering and modelling the TGF-β signalling interplays specifying the dorsal-ventral axis of the sea urchin embryo

UPMaBoSS: a novel framework for dynamic cell population modeling

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