ArticleBMC bioinformatics2020
Cells in Silico - introducing a high-performance framework for large-scale tissue modeling.
Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Leveraging experimental vasculature data for high-resolution brain tumor simulations.Biophysical journal · 2026Article
- Who's afraid of synthetic data? Hybrid approaches to deliver medical digital twins.Informatics in medicine unlocked · 2026Article
- FromFrontiers in molecular biosciences · 2024Article
- Multiscale Modeling of Spheroid Tumors: Effect of Nutrient Availability on Tumor Evolution.The journal of physical chemistry. B · 2023Article
- Development of a scoring function for comparing simulated and experimental tumor spheroids.PLoS computational biology · 2023Article
- Bayesian calibration of a stochastic, multiscale agent-based model for predicting in vitro tumor growth.PLoS computational biology · 2021Article
- Assembly of Multi-Spheroid Cellular Architectures by Programmable Droplet Merging.Advanced materials (Deerfield Beach, Fla.) · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDiscoveries in cellular dynamics and tissue development constantly reshape our understanding of fundamental biological processes such as embryogenesis, wound-healing, and tumorigenesis. High-quality microscopy data and ever-improving understanding of single-cell effects rapidly accelerate new discoveries. Still, many computational models either describe few cells highly detailed or larger cell ensembles and tissues more coarsely. Here, we connect these two scales in a joint theoretical model.
resultsWe developed a highly parallel version of the cellular Potts model that can be flexibly applied and provides an agent-based model driving cellular events. The model can be modular extended to a multi-model simulation on both scales. Based on the NAStJA framework, a scaling implementation running efficiently on high-performance computing systems was realized. We demonstrate independence of bias in our approach as well as excellent scaling behavior.
conclusionsOur model scales approximately linear beyond 10,000 cores and thus enables the simulation of large-scale three-dimensional tissues only confined by available computational resources. The strict modular design allows arbitrary models to be configured flexibly and enables applications in a wide range of research questions. Cells in Silico (CiS) can be easily molded to different model assumptions and help push computational scientists to expand their simulations to a new area in tissue simulations. As an example we highlight a 1000
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.