Hierarchical Stochastic Simulation Algorithm for SBML Models of Genetic Circuits. Journal Article uri icon



  • This paper describes a hierarchical stochastic simulation algorithm, which has been implemented within iBioSim, a tool used to model, analyze, and visualize genetic circuits. Many biological analysis tools flatten out hierarchy before simulation, but there are many disadvantages associated with this approach. First, the memory required to represent the model can quickly expand in the process. Second, the flattening process is computationally expensive. Finally, when modeling a dynamic cellular population within iBioSim, inlining the hierarchy of the model is inefficient since models must grow dynamically over time. This paper discusses a new approach to handle hierarchy on the fly to make the tool faster and more memory-efficient. This approach yields significant performance improvements as compared to the former flat analysis method.

publication date

  • January 1, 2014

has restriction

  • gold

Date in CU Experts

  • October 28, 2020 2:57 AM

Full Author List

  • Watanabe LH; Myers CJ

author count

  • 2

Other Profiles

International Standard Serial Number (ISSN)

  • 2296-4185

Additional Document Info

start page

  • 55


  • 2