Computational speed-up of large-scale, single-cell model simulations via a fully integrated SBML-based format.

Mutsuddy A, Erdem C, Huggins JR, Salim M, Cook D, Hobbs N, Feltus FA, Birtwistle MR

Bioinform Adv 3 (1) vbad039 [2023-03-23; online 2023-03-23]

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. Fully deterministic speed-up facilitates model initialization, parameter estimation and sensitivity analysis tasks. Source code is freely available at implemented in python, and supported on Linux, Windows and MacOS (via Docker).

Cemal Erdem

DDLS Fellow

PubMed 37020976

DOI 10.1093/bioadv/vbad039

Crossref 10.1093/bioadv/vbad039

pmc: PMC10070034
pii: vbad039

Publications 9.5.0