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:author: Thomas R. Sokolowski, Koichi Takahashi === eGFRD2 Prototype === originally based on the E-Cell Particle Dynamics Prototype Copyright (C) 2009-2017 AMOLF Copyright (C) 2008-2010 RIKEN Copyright (C) 2005-2008 The Molecular Sciences Institute About this package ======================== This package is tentatively named "eGFRD2 Prototype", and was originally forked from RIKEN's E-Cell Particle Dynamics Prototype (EPDP). It currently implements the enhanced Greens Function Reaction Dynamics (eGFRD) algorithm working in all dimensions, the Reaction Brownian Dynamics (RBD) simulation algorithm, and another BD simulator based on the Rection Volume Method (rvm-BD). Implementation of the original version of GFRD will possibly be added in future. The code was designed and implemented with the hope that it will eventually be part of the "E-Cell System Version 4" multi-algorithm, multi-space simulation platform, or its subsequent versions. The purpose of this prototype code written in mixed Python and C++ is to establish a solid and practical implementation of the algorithms, and to extend it into a form that is suitable for large-scale biochemical and cell simulations. The eGFRD algorithm first appeared and was used in a paper by Takahashi, Tanase-Nicola and ten Wolde . A detailed introduction to eGFRD, and in particular a description of the extensions to lower dimensions is found in the PhD Thesis of Sokolowski . Review  also contains a good introduction into the current eGFRD version. Moreover, eGFRD2 is described in detail in a forthcoming paper, currently available as a preprint on arXiv . The Reaction Brownian Dynamics algorithm is described in a paper by Morrelli and ten Wolde ; the Reaction Volume Method and rvm-BD are described in detail in the Master's Thesis of Paijmans , and also briefly in [2-4]. Authors ======================== (alphabetical order) Laurens Bossen Kazunari Kaizu Moriyoshi Koizumi Thomas Miedema Joris Paijmans Thomas R. Sokolowski Koichi Takahashi Martijn Wehrens License ======================== This package is distributed under the terms of GNU General Public License version 2. See COPYING. Building this package ======================== See INSTALL. History of the Code ======================== Koichi Takahashi initially stated development of the code in 2005 to implement his prototype of Greens Function Reaction Dynamics simulation method invented by Jeroen van Zon and Pieter Rein ten Wolde in AMOLF, Amsterdam . He gave a brief invited talk about performance evaluation and applicability of the method to yeast pheromon response pathway (the Alpha pathway) using the prototype in the Third Annual Alpha Project Research Symposium (June 16-27, 2005, at UC Berkeley Art Museum). Later, in December 2006, ten Wolde, Tanase-Nicola, and Takahashi introduced the concept called first-passage processes [8,9] to Greens Function Reaction Dynamics by putting protective domains around particles to further boost the performance and accuracy of the method. The new method was named eGFRD (enhanced Greens Function Reaction Dynamics). By 2010, it was implemented for simulating particle-based reaction-diffusion systems in 3D, and fully integrated with a BD fallback system; the framework was applied to study details of enzymatic reactions in the MAPK push-pull networks . Starting from 2009, Sokolowski, Bossen, Miedema and ten Wolde began to derive the Green's functions and implementing the new domains needed for extending eGFRD to lower dimensions. Later Paijmans and Wehrens joined these efforts. Since extension of RBD to lower dimensions turned out to be difficult, Paijmans and ten Wolde devised rvm-BD, a new BD simulation method that preserves detailed balance, based on the Reaction Volume Method (described in more detail in [6, 2-4]). All extensions to lower dimensions were assembled together by Bossen and Sokolowski in 2012-2013. In 2013, Sokolowski created a first working prototype comprising all new features mentioned above. In the following years, this prototype was tested and improved, and some further new features, such as the option of transiting particles between cylinders and planes, were integrated. The prototype code then was used to simulate an idealized model of Pom1 gradient formation, as described in . Plans ========================= Some features planned to be added are: - outsourcing further core routines from Python to C++ - optimistic discrete-event scheduling for massive parallelization - connections to non-spatial simulation methods such as ODE and Gillespie methods - more efficient visualizers / visualization interfaces References =========================  K. Takahashi, S. Tanase-Nicola and P.R. ten Wolde, PNAS doi:10.1073/pnas.0906885107 (2010).  T.R. Sokolowski, "A Computational Study of Robust Formation of Spatial Protein Patterns", PhD Thesis, VU Amsteram, ISBN: 978-90-77209-72-1 (2013).  T.R. Sokolowski and P.R. ten Wolde, arXiv:1705.08669 [q-bio.MN] (2017).  T.R. Sokolowski et al., arXiv:1708.09364 [q-bio.MN] (2017).  M.J. Morelli and P.R. ten Wolde, J. Chem. Phys. 7;129(5):054112 (2008).  J. Paijmans, Master's Thesis, University of Amsterdam (2012).  van Zon and ten Wolde, Phys. Rev. Lett. 94 (2005).  T. Opplestrup, V.V. Bulatov, G.H. Gilmer, M.H. Kalos, and B. Sadigh, Phys. Rev. Lett. 97 (2006).  M.H. Kalos, D. Levesque and L. Verlet, Phys. Rev. A 9 (1974).