Computational Speed-Up of Large-Scale, Single-Cell Model Simulations Via a Fully-Integrated SBML-Based Format
preprint
OA: closed
CC-BY-ND-4.0
Abstract
Summary Large-scale and whole-cell modeling has multiple challenges, including scalable model building and module communication bottlenecks (e.g. between metabolism, gene expression, signaling, etc). We previously developed an open-source, scalable format for a large-scale mechanistic model of proliferation and death signaling dynamics, but communication bottlenecks between gene expression and protein biochemistry modules remained. Here, we developed two solutions to communication bottlenecks that speed up simulation by ~4-fold for hybrid stochastic-deterministic simulations and by over 100-fold for fully deterministic simulations. Availability and Implementation Source code is freely available at https://github.com/birtwistlelab/SPARCED/releases/tag/v1.1.0 implemented in python, and supported on Linux, Windows, and MacOS (via Docker). Contact Marc Birtwistle [email protected] Supplementary information N/A
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- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-ND-4.0