pSSAlib: The partial-propensity stochastic chemical network simulator

Research output: Contribution to journalResearch articleContributedpeer-review



Chemical reaction networks are ubiquitous in biology, and their dynamics is fundamentally stochastic. Here, we present the software library pSSAlib, which provides a complete and concise implementation of the most efficient partial-propensity methods for simulating exact stochastic chemical kinetics. pSSAlib can import models encoded in Systems Biology Markup Language, supports time delays in chemical reactions, and stochastic spatiotemporal reaction-diffusion systems. It also provides tools for statistical analysis of simulation results and supports multiple output formats. It has previously been used for studies of biochemical reaction pathways and to benchmark other stochastic simulation methods. Here, we describe pSSAlib in detail and apply it to a new model of the endocytic pathway in eukaryotic cells, leading to the discovery of a stochastic counterpart of the cut-out switch motif underlying early-to-late endosome conversion. pSSAlib is provided as a stand-alone command-line tool and as a developer API. We also provide a plug-in for the SBMLToolbox. The open-source code and pre-packaged installers are freely available from


Original languageEnglish
Article numbere1005865
Pages (from-to)1075-1100
Number of pages26
JournalPLoS Computational Biology
Issue number12
Publication statusPublished - Dec 2017

External IDs

Scopus 85039561690
researchoutputwizard legacy.publication#82534
ORCID /0000-0003-0137-5106/work/142244211
ORCID /0000-0003-4414-4340/work/142252129


ASJC Scopus subject areas


  • SSAlib: The partial-propensity stochastic chemical network simulator