Performance analysis of a computational off-lattice tumor growth model

Kiss, Daniel; Lovrics, Anna

doi:10.1109/nc.2017.8263270

Cited by 2 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is also have to be mentioned, that high motility or aggressive duplication strategy of the agents makes the simulation slightly slower, especially for large and dense clusters. This effect could be compensated by a selection heuristic we recently presented for an off-lattice agent based model [18].…”

Section: Resultsmentioning

confidence: 99%

Simulating Solid Tumors with a Microenvironment-Coupled Agent-Based Computational Model

Kiss

Lovrics

2018

Acta Universitatis Sapientiae Electrical and Mechanical Engineering

Self Cite

View full text Add to dashboard Cite

In this paper, we introduce a three-dimensional lattice-based computational model in which every lattice point can be occupied by an agent of various types (e.g. cancer cell, blood vessel cell or extracellular matrix). The behavior of agents can be associated to different chemical compounds that obey mass-transfer laws such as diffusion and decay in the surrounding environment. Furthermore, agents are also able to produce and consume chemical compounds. After a detailed description, the capabilities of the model are demonstrated by presenting and discussing a simulation of a biological experiment available in the literature.

show abstract

Section: Resultsmentioning

confidence: 99%

Simulating Solid Tumors with a Microenvironment-Coupled Agent-Based Computational Model

Kiss

Lovrics

2018

Acta Universitatis Sapientiae Electrical and Mechanical Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…We used a simplified version of the model introduced by Drasdo et al [8] and previously presented in [11]. This model uses the position, mean diameter, core ratio, adhesive ratio, adhesion factor and velocity data of each individual.…”

Section: Agent-based Modelingmentioning

confidence: 99%

Evaluation of colony formation dataset of simulated cell cultures

Kiss¹,

Kertész²,

Jaskó³

et al. 2020

AMI

Self Cite

View full text Add to dashboard Cite

In vitro biological experiments and in silico individual-based computational models are widely used to understand the low-level behavior of cells and cellular functions. Many of these functions can not be directly observed, however, may be deduced from other properties that can be well measured and modeled. In this paper, we present a procedure to evaluate synthetic cell colony formation generated by an off-lattice individual-based model. The calculated shape features of the artificial cell aggregates can be related to the parameter values of the simulated agents, therefore this data can be used to quantify properties of real-life cells such as motility or binding affinity that can not be easily determined otherwise. Our experiments showed that only a few of these parameters are responsible for the difference in shape features of the colonies.

show abstract

Performance analysis of a computational off-lattice tumor growth model

Cited by 2 publications

References 9 publications

Simulating Solid Tumors with a Microenvironment-Coupled Agent-Based Computational Model

Simulating Solid Tumors with a Microenvironment-Coupled Agent-Based Computational Model

Evaluation of colony formation dataset of simulated cell cultures

Contact Info

Product

Resources

About