NL4Py: Agent-based modeling in Python with parallelizable NetLogo workspaces

Gunaratne, Chathika; Garibay, Iván

doi:10.1016/j.softx.2021.100801

Cited by 14 publications

(6 citation statements)

References 19 publications

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“…This approach was used to account for stochasticity of the ABM and EA and to reduce the likelihood of the EA becoming stuck in local error minima. We developed our own Python script for the EA and used the NL4Py Python library [ 80 ] to enable communication between Python and NetLogo. To improve run time, our EA implementation ran the ABM in parallel across multiple computing units.…”

Section: Methodsmentioning

confidence: 99%

A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion

et al. 2022

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Physiological and pathological processes including embryogenesis and tumorigenesis rely on the ability of individual cells to work collectively to form multicell patterns. In these heterogeneous multicell systems, cell-cell signaling induces differential adhesion between cells that leads to tissue-level patterning. However, the sensitivity of pattern formation to changes in the strengths of signaling or cell adhesion processes is not well understood. Prior work has explored these issues using synthetically engineered heterogeneous multicell spheroid systems, in which cell subpopulations engage in bidirectional intercellular signaling to regulate the expression of different cadherins. While engineered cell systems provide excellent experimental tools to observe pattern formation in cell populations, computational models of these systems may be leveraged to explore more systematically how specific combinations of signaling and adhesion parameters can drive the emergence of unique patterns. We developed and validated two- and three-dimensional agent-based models (ABMs) of spheroid patterning for previously described cells engineered with a bidirectional signaling circuit that regulates N- and P-cadherin expression. Systematic exploration of model predictions, some of which were experimentally validated, revealed how cell seeding parameters, the order of signaling events, probabilities of induced cadherin expression, and homotypic adhesion strengths affect pattern formation. Unsupervised clustering was also used to map combinations of signaling and adhesion parameters to these unique spheroid patterns predicted by the ABM. Finally, we demonstrated how the model may be deployed to design new synthetic cell signaling circuits based on a desired final multicell pattern.

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Section: Methodsmentioning

confidence: 99%

A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion

et al. 2022

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“…For Gunaratne & Garibay, (2021) data are the most significant unit in any study. The supply of data is used as inputs in the analysis depending on the requirements of the analysis.…”

Section: Methodsmentioning

confidence: 99%

Analysis of the use of the Python programming language for statistical calculations.

Naranjo

Brito

Núñez

et al. 2022

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This article presents a review of the use of Python for data analysis. It discusses the main specialized libraries and the advantages of using Python for data analysis. Also, the main phases of data analysis are explained in general and in an example with the programming language. It is concluded that Python presents multiple advantages in its use and that in spite of being an open source software, it allows professional and sophisticated work in data management and statistical calculations.

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“…Netlogo is pre-loaded with a relatively large library consisting of models that help researchers run simulations to address problems and explore various aspects [36]. By simulating the interaction between multiple individuals, many complex phenomena, such as ant colony, bird colony, ecosystems, apartheids, and virus transmission can emerge [37]. The simulated world is composed of subjects, which can accept commands and then carry out corresponding behaviors, and the behaviors of all subjects occur in parallel.…”

Section: Distribution Of Occupants In Spacementioning

confidence: 99%

Risk Assessment and Prevention Strategy of Virus Infection in the Context of University Resumption

et al. 2022

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The risk assessment system of virus infection probability and the prevention measures for virus transmission are keys to controlling epidemics. In the context of university resumption, this study identifies the risk elements in terms of the mechanism of virus transmission. The effect of two recognized effective measures, i.e., occupancy constraints and ventilation intervention, on the infection risk are quantified and compared using the improved Wells–Riley model. Considering the priority of these two measures, the controlling quantity are determined, and the optimal schemes are proposed based on the targeted infection risk. The results show that the effect of reducing infection risk by constraining occupancy within 25% of all public campus buildings is better than that achieved by increasing the ventilation rate alone. If the ventilation system of the building type is operated by occupiers, it is a priority to prevent the risk of virus infection by restricting occupancy and ensuring the distance between occupants, while if the ventilation system of the building type is centrally controlled, it is a priority to increase the ventilation rate and then limit the occupancy rate during peak periods to 75%.

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NL4Py: Agent-based modeling in Python with parallelizable NetLogo workspaces

Cited by 14 publications

References 19 publications

A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion

A computational modeling approach for predicting multicell spheroid patterns based on signaling-induced differential adhesion

Analysis of the use of the Python programming language for statistical calculations.

Risk Assessment and Prevention Strategy of Virus Infection in the Context of University Resumption

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