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Where spatial effects play a prominent role the complex morphology of cells may have to be represented, along with aspects such as chemical localization and diffusion. This high level of detail makes efficiency a particularly important consideration for software that is designed to simulate such systems.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We describe STEPS, a stochastic reaction\u2013diffusion simulator developed with an emphasis on simulating biochemical signaling pathways accurately and efficiently. STEPS supports all the above-mentioned features, and well-validated support for SBML allows many existing biochemical models to be imported reliably. Complex boundaries can be represented accurately in externally generated 3D tetrahedral meshes imported by STEPS. The powerful Python interface facilitates model construction and simulation control. STEPS implements the composition and rejection method, a variation of the Gillespie SSA, supporting diffusion between tetrahedral elements within an efficient search and update engine. Additional support for well-mixed conditions and for deterministic model solution is implemented. Solver accuracy is confirmed with an original and extensive validation set consisting of isolated reaction, diffusion and reaction\u2013diffusion systems. Accuracy imposes upper and lower limits on tetrahedron sizes, which are described in detail. By comparing to Smoldyn, we show how the voxel-based approach in STEPS is often faster than particle-based methods, with increasing advantage in larger systems, and by comparing to MesoRD we show the efficiency of the STEPS implementation.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>STEPS simulates models of cellular reaction\u2013diffusion systems with complex boundaries with high accuracy and high performance in C\/C++, controlled by a powerful and user-friendly Python interface. STEPS is free for use and is available at <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/steps.sourceforge.net\/\" ext-link-type=\"uri\">http:\/\/steps.sourceforge.net\/<\/jats:ext-link>\n            <\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1752-0509-6-36","type":"journal-article","created":{"date-parts":[[2012,5,10]],"date-time":"2012-05-10T16:14:24Z","timestamp":1336666464000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":137,"title":["STEPS: efficient simulation of stochastic reaction\u2013diffusion models in realistic morphologies"],"prefix":"10.1186","volume":"6","author":[{"given":"Iain","family":"Hepburn","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weiliang","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Wils","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erik","family":"De Schutter","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2012,5,10]]},"reference":[{"key":"939_CR1","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1016\/S0896-6273(03)00639-1","volume":"40","author":"GJ Augustine","year":"2003","unstructured":"Augustine GJ, Santamaria F, Tanaka K: Local calcium signaling in neurons. 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