Skip to main content
SpringerLink
Log in
Book cover

Encyclopedia of Computational Neuroscience pp 1–4Cite as

STEPS: STochastic Engine for Pathway Simulation

  • 200 Accesses

Definition

STEPS (Hepburn et al. 2012) is a molecular simulator designed to simulate neuronal signaling pathways in dendrites and around synapses but can also be applied to other biochemical networks. STEPS simulates such systems to a high level of detail by supporting complex morphology, stochastic kinetics, spatial concentration gradients, and diffusion. For reasons of efficiency STEPS employs the subvolume discretization approach based on Gillespie’s stochastic simulation algorithm (Gillespie 1977), rather than particle-tracking methods.

Since version 2.0 STEPS also supports accurate computation of local membrane potentials Hepburn et al. (2013). Tight integration with the reaction-diffusion calculations allows detailed, accurate, and relatively efficient coupling between the molecular and the electrical components of cell signaling.

Binaries and source code are released under the GNU General Public License (version 3) and are available at http://steps.sourceforge.net.

Detailed...

This is a preview of subscription content, log in via an institution.

References

  • Augustine GJ, Santamaria F, Tanaka K (2003) Local calcium signaling in neurons. Neuron 40:331–346

    Article  CAS  PubMed  Google Scholar 

  • Berridge MJ, Lipp P, Bootman MD (2000) The versatility and universality of calcium signaling. Nat Rev Mol Cell Bio 1:11–21

    Article  CAS  Google Scholar 

  • Bhalla US, Bilitch DH, Bower JM (1992) Rallpacks: a set of benchmarks for neuronal simulators. Trends Neurosci 15:453–458

    Article  CAS  PubMed  Google Scholar 

  • Gillespie DT (1977) Exact stochastic simulation of coupled chemical-reactions. J Phys Chem-US 81:2340–2361

    Article  CAS  Google Scholar 

  • Hepburn I, Chen W, Wils S, De Schutter E (2012) STEPS: efficient simulation of stochastic reaction-diffusion models in realistic morphologies. BMC Syst Biol 6:36

    Article  PubMed Central  PubMed  Google Scholar 

  • Hepburn I, Cannon R and De Schutter E (2013) Efficient calculation of the quasi-static electrical potential on a tetrahedral mesh and its implementation in STEPS. Front Comput Neurosci 7:129

    PubMed Central  PubMed  Google Scholar 

  • Hucka M, Finney A, Sauro HM, Bolouri H, Doyle JC, Kitano H, Arkin AP, Bornstein BJ, Bray D, Cornish-Bowden A, Cuellar AA, Dronov S, Gilles ED, Ginkel M, Gor V, Goryanin II, Hedley WJ, Hodgman TC, Hofmeyr JH, Hunter PJ, Juty NS, Kasberger JL, Kremling A, Kummer U, Le Novère N, Loew LM, Lucio D, Mendes P, Minch E, Mjolsness ED, Nakayama Y, Nelson MR, Nielsen PF, Sakurada T, Schaff JC, Shapiro BE, Shimizu TS, Spence HD, Stelling J, Takahashi K, Tomita M, Wagner J, Wang J (2003) The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. Bioinformatics 19:524–531

    Article  CAS  PubMed  Google Scholar 

  • Lindsay KA, Rosenberg JR, Tucker G (2004) From Maxwell’s equations to the cable equation and beyond. Prog Biophys Mol Bio 85:71–116

    Article  CAS  Google Scholar 

  • Rizzuto R, Pozzan T (2006) Microdomains of intracellular Ca2+: molecular determinants and functional consequences. Physiol Rev 86:369–408

    Article  CAS  PubMed  Google Scholar 

  • Santamaria F, Wils S, De Schutter E, Augustine GJ (2006) Anomalous diffusion in Purkinje cell dendrites caused by spines. Neuron 52:635–648

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Wils S, De Schutter E (2009) STEPS: modeling and simulating complex reaction-diffusion systems with Python. Front Neuroinform 3:15

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computational Neuroscience Unit, Okinawa Institute of Science and Technology, Onna-son, Okinawa, Japan

    Iain Hepburn

  2. Theoretical Neurobiology, University of Antwerp, Antwerp, Belgium

    Iain Hepburn

Authors
  1. Iain Hepburn
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Iain Hepburn .

Editor information

Editors and Affiliations

  1. Atlanta, Georgia, USA

    Dieter Jaeger

  2. Department of Biomedical Engineering, Florida International University, Miami, Florida, USA

    Ranu Jung

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this entry

Cite this entry

Hepburn, I. (2013). STEPS: STochastic Engine for Pathway Simulation. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_262-7

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-7320-6_262-7

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4614-7320-6

  • eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

Publish with us

Policies and ethics

Chapter history

  1. Latest

    STEPS: STochastic Engine for Pathway Simulation
    Published:
    11 January 2020

    DOI: https://doi.org/10.1007/978-1-4614-7320-6_262-8

  2. Original

    STEPS: STochastic Engine for Pathway Simulation
    Published:
    01 March 2014

    DOI: https://doi.org/10.1007/978-1-4614-7320-6_262-7

Search

Navigation