STEPS

STochastic Engine for Pathway Simulation

Articles about STEPS Development:

  • I. Hepburn, W. Chen and E. De Schutter (2016) Accurate reaction-diffusion operator splitting on tetrahedral meshes for parallel stochastic molecular simulations. The Journal of Chemical Physics, 145, 054118. (Parallelization)

  • W. Chen and E. De Schutter (2014) Python-based geometry preparation and simulation visualization toolkit for STEPS. Frontiers in Neuroinformatics 8:37. (Utilities, Visualization)

  • I. Hepburn, R. Cannon and E. De Schutter. (2013) Efficient calculation of the quasi-static electrical potential on a tetrahedral mesh and its implementation in STEPS. Frontiers in Computational Neuroscience 7:129. (Electrical field simulation)

  • I. Hepburn, W. Chen, S. Wils and E. De Schutter (2012) STEPS: Efficient simulation of stochastic reaction-diffusion models in realistic morphologies. BMC Systems Biology, 6:36. (Software infrastructure, Reaction-diffusion simulation)

  • S. Wils and E. De Schutter (2009) STEPS: Modeling and simulating complex reaction-diffusion systems with Python. Frontiers in Neuroinformatics 3:15. (Software infrastructure, Reaction-diffusion simulation)

Published modelling studies that use STEPS:

  • Schelker M, Mair CM, Jolmes F, Welke RW, Klipp E, et al. (2016) Viral RNA Degradation and Diffusion Act as a Bottleneck for the Influenza A Virus Infection Efficiency. PLoS Comput Biol 12(10): e1005075. doi: 10.1371/journal.pcbi.1005075

  • Mohapatra, N., Tønnesen, J., Vlachos, A., Kuner, T., Deller, T., Nägerl, U.V., Santamaria, F. and Jedlicka, P., 2016. Spines slow down dendritic chloride diffusion and affect short-term ionic plasticity of GABAergic inhibition. Scientific Reports, 6, p.23196.

  • Matolcsi, M. and Giordano, N., 2015. A Novel Explanation for Observed CaMKII Dynamics in Dendritic Spines with Added EGTA or BAPTA. Biophysical journal, 108(4), pp.975-985.

  • H. Anwar, C.J. Roome, H. Nedelescu, W. Chen, B. Kuhn, E. De Schutter. (2014) Dendritic diameters affect the spatial variability of intracellular calcium dynamics in computer models. Frontiers in Cellular Neuroscience. 2014;8:168. doi:10.3389/fncel.2014.00168.

  • H. Anwar, I. Hepburn, H. Nedelescu, W. Chen and E. De Schutter. (2013) Stochastic calcium mechanisms cause dendritic calcium spike variability. J Neurosci 33(40):15848-67.

  • I. Hepburn, R. Cannon and E. De Schutter. (2013) Efficient calculation of the quasi-static electrical potential on a tetrahedral mesh and its implementation in STEPS. Front. Comput. Neurosci. 7:129. doi: 10.3389/fncom.2013.00129.

  • K. Hituri and M.L. Linne (2013) Comparison of models for IP3 receptor kinetics using stochastic simulations. PLoS One 8(4):e59618

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

  • G. Antunes and E. De Schutter (2012) A Stochastic Signaling Network Mediates the Probabilistic Induction of Cerebellar Long-Term Depression. The Journal of Neuroscience 32(27): 9288-9300

  • S. G. Tewari (2011) Stochastic Simulation of a Dimer Sodium Pump. Journal of Biological Systems 19(4):551

  • S. Wils and E. De Schutter (2009) STEPS: Modeling and simulating complex reaction-diffusion systems with Python. Frontiers in Neuroinformatics 3: 15 (2009)