References

1: J Garcia de la Torre. Building hydrodynamic bead–shell models for rigid bioparticles of arbitrary shape. Biophysical Chemistry, 94(3):265–274, dec 2001. doi:10.1016/s0301-4622(01)00244-7.
2: Beatriz Carrasco and José Garc\'ıa de la Torre. Hydrodynamic properties of rigid particles: comparison of different modeling and computational procedures. Biophysical Journal, 76(6):3044–3057, jun 1999. doi:10.1016/s0006-3495(99)77457-6.
3: Michael P. Allen and Dominic J. Tildesley. Computer Simulation of Liquids. Oxford University Press, nov 2017. doi:10.1093/oso/9780198803195.001.0001.
4: V. Ogarko and S. Luding. A fast multilevel algorithm for contact detection of arbitrarily polydisperse objects. Computer Physics Communications, 183(4):931–936, apr 2012. doi:10.1016/j.cpc.2011.12.019.
5: John Amanatides and Andrew Woo. A fast voxel traversal algorithm for ray tracing. In In Eurographics ’87, 3–10. 1987.
6: Christer Ericson. Real-Time Collision Detection. CRC Press, dec 2004. doi:10.1201/b14581.
7: Tomas Möller and Ben Trumbore. Fast, minimum storage ray-triangle intersection. Journal of Graphics Tools, 2(1):21–28, jan 1997. doi:10.1080/10867651.1997.10487468.
8: Tomas Akenine-Möllser. Fast 3d triangle-box overlap testing. Journal of Graphics Tools, 6(1):29–33, jan 2001. doi:10.1080/10867651.2001.10487535.
9: David Eberly. 3D Game Engine Design. Morgan Kaufmann Publishers, 2001.
10: Rex A. Kerr, Thomas M. Bartol, Boris Kaminsky, Markus Dittrich, Jen-Chien Jack Chang, Scott B. Baden, Terrence J. Sejnowski, and Joel R. Stiles. Fast monte carlo simulation methods for biological reaction-diffusion systems in solution and on surfaces. SIAM Journal on Scientific Computing, 30(6):3126–3149, jan 2008. doi:10.1137/070692017.
11: Joel Stiles and Thomas Bartol. Monte Carlo Methods for Simulating Realistic Synaptic Microphysiology Using MCell, pages 87–127. CRC Press, 2001. doi:10.1201/9781420039290.ch4.
12: Radek Erban, Jonathan Chapman, and Philip Maini. A practical guide to stochastic simulations of reaction-diffusion processes. 2007. doi:10.48550/ARXIV.0704.1908.
13: Ioana M. Ilie, Wim J. Briels, and Wouter K. den Otter. An elementary singularity-free rotational brownian dynamics algorithm for anisotropic particles. The Journal of Chemical Physics, 142(11):114103, mar 2015. doi:10.1063/1.4914322.
14: Marc Niethammer, Raul San Jose Estepar, Sylvain Bouix, Martha Shenton, and Carl-Fredrik Westin. On diffusion tensor estimation. In 2006 International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, aug 2006. doi:10.1109/iembs.2006.259826.
15: Steven Harvey and Jose Garcia de la Torre. Coordinate systems for modeling the hydrodynamic resistance and diffusion coefficients of irregularly shaped rigid macromolecules. Macromolecules, 13(4):960–964, jul 1980. doi:10.1021/ma60076a037.
16: B. Carrasco and J. Garcı\'a de la Torre. Improved hydrodynamic interaction in macromolecular bead models. The Journal of Chemical Physics, 111(10):4817–4826, sep 1999. doi:10.1063/1.479743.
17: J K G Dhont. An Introduction to Dynamics of Colloids. Elsevier, 1996. doi:10.1016/s1383-7303(96)x8001-3.
18: Jose Garcia De La Torre and Victor A. Bloomfield. Hydrodynamic properties of macromolecular complexes. i. translation. Biopolymers, 16(8):1747–1763, aug 1977. doi:10.1002/bip.1977.360160811.
19: J. Garc\'ıa de la Torre, G. del Rio Echenique, and A. Ortega. Improved calculation of rotational diffusion and intrinsic viscosity of bead models for macromolecules and nanoparticles. The Journal of Physical Chemistry B, 111(5):955–961, jan 2007. doi:10.1021/jp0647941.
20: José Garc\'ıa de la Torre and Vicente Rodes. Effects from bead size and hydrodynamic interactions on the translational and rotational coefficients of macromolecular bead models. The Journal of Chemical Physics, 79(5):2454–2460, sep 1983. doi:10.1063/1.446054.
21: V. Varadarajan. Supersymmetry for Mathematicians: An Introduction. American Mathematical Society, jul 2004. doi:10.1090/cln/011.
22: P Deligne and J Morgan. Notes on supersymmetry following Bernstein. Quantum ﬁelds and strings; a course for mathematicians, pages 41–96. Volume 1. Amer. Math. Soc, Princeton, NJ; Providence, RI, 1996.
23: Moritz Hoffmann, Christoph Fröhner, and Frank Noé. ReaDDy 2: fast and flexible software framework for interacting-particle reaction dynamics. PLOS Computational Biology, 15(2):e1006830, feb 2019. doi:10.1371/journal.pcbi.1006830.
24: M Doi. Stochastic theory of diffusion-controlled reaction. Journal of Physics A: Mathematical and General, 9(9):1479–1495, sep 1976. doi:10.1088/0305-4470/9/9/009.
25: M. Corsini, P. Cignoni, and R. Scopigno. Efficient and flexible sampling with blue noise properties of triangular meshes. IEEE Transactions on Visualization and Computer Graphics, 18(6):914–924, jun 2012. doi:10.1109/tvcg.2012.34.
26: Robert Osada, Thomas Funkhouser, Bernard Chazelle, and David Dobkin. Shape distributions. ACM Transactions on Graphics, 21(4):807–832, oct 2002. doi:10.1145/571647.571648.
27: Robert Bridson. Fast poisson disk sampling in arbitrary dimensions. In ACM SIGGRAPH 2007 sketches on - SIGGRAPH \textquotesingle 07. ACM Press, 2007. doi:10.1145/1278780.1278807.
28: David Kirk. Graphics Gems III (IBM Version). Elsevier Science & Techn., December 2012. URL: https://www.ebook.de/de/product/21119786/david_kirk_graphics_gems_iii_ibm_version.html.
29: J. R. Espinosa, C. Vega, and E. Sanz. The mold integration method for the calculation of the crystal-fluid interfacial free energy from simulations. The Journal of Chemical Physics, 141(13):134709, oct 2014. doi:10.1063/1.4896621.
30: Jorge R. Espinosa, Adiran Garaizar, Carlos Vega, Daan Frenkel, and Rosana Collepardo-Guevara. Breakdown of the law of rectilinear diameter and related surprises in the liquid-vapor coexistence in systems of patchy particles. The Journal of Chemical Physics, 150(22):224510, jun 2019. doi:10.1063/1.5098551.
31: J. Jover, A. J. Haslam, A. Galindo, G. Jackson, and E. A. Müller. Pseudo hard-sphere potential for use in continuous molecular-dynamics simulation of spherical and chain molecules. The Journal of Chemical Physics, 137(14):144505, oct 2012. doi:10.1063/1.4754275.
32: Erich A. Muller, Åsmund Ervik, and Andrés Mej\'ıa. A guide to computing interfacial properties of fluids from molecular simulations [article v1.0]. Living Journal of Computational Molecular Science, 2020. doi:10.33011/livecoms.2.1.21385.
33: Carolina Baruffi, Alphonse Finel, Yann Le Bouar, Brigitte Bacroix, and Oguz Umut Salman. Overdamped langevin dynamics simulations of grain boundary motion. Materials Theory, may 2019. doi:10.1186/s41313-019-0016-1.
34: Peter Shirley, Michael Ashikhmin, and Steve Marschner. Fundamentals of Computer Graphics. A K Peters/CRC Press, jul 2009. doi:10.1201/9781439865521.
35: Jens Glaser, Xun Zha, Joshua A. Anderson, Sharon C. Glotzer, and Alex Travesset. Pressure in rigid body molecular dynamics. Computational Materials Science, 173:109430, feb 2020. doi:10.1016/j.commatsci.2019.109430.
36: Jelena Baranovic. AMPA receptors in the synapse: very little space and even less time. Neuropharmacology, 196:108711, sep 2021. doi:10.1016/j.neuropharm.2021.108711.
37: Hiroki Tanaka, Naoyuki Miyazaki, Kyoko Matoba, Terukazu Nogi, Kenji Iwasaki, and Junichi Takagi. Higher-order architecture of cell adhesion mediated by polymorphic synaptic adhesion molecules neurexin and neuroligin. Cell Reports, 2(1):101–110, jul 2012. doi:10.1016/j.celrep.2012.06.009.
38: Andreas Frick, Jeffrey Magee, and Daniel Johnston. LTP is accompanied by an enhanced local excitability of pyramidal neuron dendrites. Nature Neuroscience, 7(2):126–135, jan 2004. doi:10.1038/nn1178.
39: John Lisman, Ryohei Yasuda, and Sridhar Raghavachari. Mechanisms of CaMKII action in long-term potentiation. Nature Reviews Neuroscience, 13(3):169–182, feb 2012. URL: https://doi.org/10.1038/nrn3192, doi:10.1038/nrn3192.
40: Seok-Jin R. Lee, Yasmin Escobedo-Lozoya, Erzsebet M. Szatmari, and Ryohei Yasuda. Activation of CaMKII in single dendritic spines during long-term potentiation. Nature, 458(7236):299–304, mar 2009. URL: https://doi.org/10.1038/nature07842, doi:10.1038/nature07842.
41: Patricio Opazo, Matthieu Sainlos, and Daniel Choquet. Regulation of AMPA receptor surface diffusion by PSD-95 slots. Current Opinion in Neurobiology, 22(3):453–460, jun 2012. URL: https://doi.org/10.1016/j.conb.2011.10.010, doi:10.1016/j.conb.2011.10.010.
42: A. C. Penn, C. L. Zhang, F. Georges, L. Royer, C. Breillat, E. Hosy, J. D. Petersen, Y. Humeau, and D. Choquet. Hippocampal LTP and contextual learning require surface diffusion of AMPA receptors. Nature, 549(7672):384–388, sep 2017. URL: https://doi.org/10.1038/nature23658, doi:10.1038/nature23658.
43: Richard L. Huganir and Roger A. Nicoll. AMPARs and synaptic plasticity: the last 25 years. Neuron, 80(3):704–717, oct 2013. URL: https://doi.org/10.1016/j.neuron.2013.10.025, doi:10.1016/j.neuron.2013.10.025.
44: Harold D. MacGillavry, Justin M. Kerr, and Thomas A. Blanpied. Lateral organization of the postsynaptic density. Molecular and Cellular Neuroscience, 48(4):321–331, dec 2011. doi:10.1016/j.mcn.2011.09.001.
45: Yugo Fukazawa, Yoshito Saitoh, Fumiko Ozawa, Yasuhiko Ohta, Kensaku Mizuno, and Kaoru Inokuchi. Hippocampal LTP is accompanied by enhanced f-actin content within the dendritic spine that is essential for late LTP maintenance in vivo. Neuron, 38(3):447–460, may 2003. doi:10.1016/s0896-6273(03)00206-x.
46: Kenichi Okamoto, Miquel Bosch, and Yasunori Hayashi. The roles of CaMKII and f-actin in the structural plasticity of dendritic spines: a potential molecular identity of a synaptic tag? Physiology, 24(6):357–366, dec 2009. doi:10.1152/physiol.00029.2009.
47: Masanori Matsuzaki, Naoki Honkura, Graham C. R. Ellis-Davies, and Haruo Kasai. Structural basis of long-term potentiation in single dendritic spines. Nature, 429(6993):761–766, jun 2004. URL: https://doi.org/10.1038/nature02617, doi:10.1038/nature02617.
48: Mikyoung Park, Esther C. Penick, Jeffrey G. Edwards, Julie A. Kauer, and Michael D. Ehlers. Recycling endosomes supply AMPA receptors for LTP. Science, 305(5692):1972–1975, sep 2004. doi:10.1126/science.1102026.
49: Mikyoung Park, Jennifer M. Salgado, Linnaea Ostroff, Thomas D. Helton, Camenzind G. Robinson, Kristen M. Harris, and Michael D. Ehlers. Plasticity-induced growth of dendritic spines by exocytic trafficking from recycling endosomes. Neuron, 52(5):817–830, dec 2006. doi:10.1016/j.neuron.2006.09.040.
50: M. A. Patterson, E. M. Szatmari, and R. Yasuda. AMPA receptors are exocytosed in stimulated spines and adjacent dendrites in a ras-ERK-dependent manner during long-term potentiation. Proceedings of the National Academy of Sciences, 107(36):15951–15956, aug 2010. URL: https://doi.org/10.1073/pnas.0913875107, doi:10.1073/pnas.0913875107.
51: Wickliffe C. Abraham and Joanna M. Williams. LTP maintenance and its protein synthesis-dependence. Neurobiology of Learning and Memory, 89(3):260–268, mar 2008. doi:10.1016/j.nlm.2007.10.001.
52: Clive R Bramham. Local protein synthesis, actin dynamics, and LTP consolidation. Current Opinion in Neurobiology, 18(5):524–531, oct 2008. doi:10.1016/j.conb.2008.09.013.
53: J. M. Kerr and T. A. Blanpied. Subsynaptic AMPA receptor distribution is acutely regulated by actin-driven reorganization of the postsynaptic density. Journal of Neuroscience, 32(2):658–673, jan 2012. doi:10.1523/jneurosci.2927-11.2012.
54: Miquel Bosch, Jorge Castro, Takeo Saneyoshi, Hitomi Matsuno, Mriganka Sur, and Yasunori Hayashi. Structural and molecular remodeling of dendritic spine substructures during long-term potentiation. Neuron, 82(2):444–459, apr 2014. URL: https://doi.org/10.1016/j.neuron.2014.03.021, doi:10.1016/j.neuron.2014.03.021.
55: Daniel Meyer, Tobias Bonhoeffer, and Volker Scheuss. Balance and stability of synaptic structures during synaptic plasticity. Neuron, 82(2):430–443, apr 2014. URL: https://doi.org/10.1016/j.neuron.2014.02.031, doi:10.1016/j.neuron.2014.02.031.
56: Yoichi Araki, Menglong Zeng, Mingjie Zhang, and Richard L. Huganir. Rapid dispersion of SynGAP from synaptic spines triggers AMPA receptor insertion and spine enlargement during LTP. Neuron, 85(1):173–189, jan 2015. doi:10.1016/j.neuron.2014.12.023.
57: Martin Hruska, Nathan Henderson, Sylvain J. Le Marchand, Haani Jafri, and Matthew B. Dalva. Synaptic nanomodules underlie the organization and plasticity of spine synapses. Nature Neuroscience, 21(5):671–682, apr 2018. doi:10.1038/s41593-018-0138-9.
58: Menglong Zeng, Yuan Shang, Yoichi Araki, Tingfeng Guo, Richard L. Huganir, and Mingjie Zhang. Phase transition in postsynaptic densities underlies formation of synaptic complexes and synaptic plasticity. Cell, 166(5):1163–1175.e12, aug 2016. doi:10.1016/j.cell.2016.07.008.
59: Menglong Zeng, Xudong Chen, Dongshi Guan, Jia Xu, Haowei Wu, Penger Tong, and Mingjie Zhang. Reconstituted postsynaptic density as a molecular platform for understanding synapse formation and plasticity. Cell, 174(5):1172–1187.e16, aug 2018. doi:10.1016/j.cell.2018.06.047.
60: Menglong Zeng, Javier D\'ıaz-Alonso, Fei Ye, Xudong Chen, Jia Xu, Zeyang Ji, Roger A. Nicoll, and Mingjie Zhang. Phase separation-mediated TARP/MAGUK complex condensation and AMPA receptor synaptic transmission. Neuron, 104(3):529–543.e6, nov 2019. doi:10.1016/j.neuron.2019.08.001.
61: Salman F. Banani, Hyun O. Lee, Anthony A. Hyman, and Michael K. Rosen. Biomolecular condensates: organizers of cellular biochemistry. Nature Reviews Molecular Cell Biology, 18(5):285–298, feb 2017. doi:10.1038/nrm.2017.7.
62: Waja Wegner, Alexander C. Mott, Seth G. N. Grant, Heinz Steffens, and Katrin I. Willig. In vivo STED microscopy visualizes PSD95 sub-structures and morphological changes over several hours in the mouse visual cortex. Scientific Reports, jan 2018. doi:10.1038/s41598-017-18640-z.
63: Jiahua Lu, Junjie Qian, Zhentian Xu, Shengyong Yin, Lin Zhou, Shusen Zheng, and Wu Zhang. Emerging roles of liquid–liquid phase separation in cancer: from protein aggregation to immune-associated signaling. Frontiers in Cell and Developmental Biology, jun 2021. doi:10.3389/fcell.2021.631486.
64: Amandine Molliex, Jamshid Temirov, Jihun Lee, Maura Coughlin, Anderson P. Kanagaraj, Hong Joo Kim, Tanja Mittag, and J. Paul Taylor. Phase separation by low complexity domains promotes stress granule assembly and drives pathological fibrillization. Cell, 163(1):123–133, sep 2015. doi:10.1016/j.cell.2015.09.015.
65: Susanne Wegmann, Bahareh Eftekharzadeh, Katharina Tepper, Katarzyna M Zoltowska, Rachel E Bennett, Simon Dujardin, Pawel R Laskowski, Danny MacKenzie, Tarun Kamath, Caitlin Commins, Charles Vanderburg, Allyson D Roe, Zhanyun Fan, Amandine M Molliex, Amayra Hernandez-Vega, Daniel Muller, Anthony A Hyman, Eckhard Mandelkow, J Paul Taylor, and Bradley T Hyman. Tau protein liquid–liquid phase separation can initiate tau aggregation. The EMBO Journal, feb 2018. doi:10.15252/embj.201798049.
66: Sang Hak Lee, Chaoyi Jin, En Cai, Pinghua Ge, Yuji Ishitsuka, Kai Wen Teng, Andre A de Thomaz, Duncan Nall, Murat Baday, Okunola Jeyifous, Daniel Demonte, Christopher M Dundas, Sheldon Park, Jary Y Delgado, William N Green, and Paul R Selvin. Super-resolution imaging of synaptic and extra-synaptic AMPA receptors with different-sized fluorescent probes. eLife, jul 2017. URL: https://doi.org/10.7554/elife.27744, doi:10.7554/elife.27744.
67: Paul Smolen, Douglas A. Baxter, and John H. Byrne. Molecular constraints on synaptic tagging and maintenance of long-term potentiation: a predictive model. PLoS Computational Biology, 8(8):e1002620, aug 2012. doi:10.1371/journal.pcbi.1002620.
68: M. E. Johnson, A. Chen, J. R. Faeder, P. Henning, I. I. Moraru, M. Meier-Schellersheim, R. F. Murphy, T. Prüstel, J. A. Theriot, and A. M. Uhrmacher. Quantifying the roles of space and stochasticity in computer simulations for cell biology and cellular biochemistry. Molecular Biology of the Cell, 32(2):186–210, jan 2021. doi:10.1091/mbc.e20-08-0530.
69: Sebastian Kmiecik, Dominik Gront, Michal Kolinski, Lukasz Wieteska, Aleksandra Elzbieta Dawid, and Andrzej Kolinski. Coarse-grained protein models and their applications. Chemical Reviews, 116(14):7898–7936, jun 2016. doi:10.1021/acs.chemrev.6b00163.
70: Gregory L Dignon, Wenwei Zheng, and Jeetain Mittal. Simulation methods for liquid–liquid phase separation of disordered proteins. Current Opinion in Chemical Engineering, 23:92–98, mar 2019. doi:10.1016/j.coche.2019.03.004.
71: Joshua A. Anderson, Jens Glaser, and Sharon C. Glotzer. HOOMD-blue: a python package for high-performance molecular dynamics and hard particle monte carlo simulations. Computational Materials Science, 173:109363, feb 2020. doi:10.1016/j.commatsci.2019.109363.
72: Gregory L. Dignon, Wenwei Zheng, Young C. Kim, Robert B. Best, and Jeetain Mittal. Sequence determinants of protein phase behavior from a coarse-grained model. PLOS Computational Biology, 14(1):e1005941, jan 2018. doi:10.1371/journal.pcbi.1005941.
73: Valentina Tozzini. Coarse-grained models for proteins. Current Opinion in Structural Biology, 15(2):144–150, apr 2005. doi:10.1016/j.sbi.2005.02.005.
74: Tihamér Geyer and Uwe Winter. An o(n2) approximation for hydrodynamic interactions in brownian dynamics simulations. The Journal of Chemical Physics, 130(11):114905, mar 2009. doi:10.1063/1.3089668.
75: Maciej Długosz and Joanna Trylska. Diffusion in crowded biological environments: applications of brownian dynamics. BMC Biophysics, mar 2011. doi:10.1186/2046-1682-4-3.
76: Donald L. Ermak and J. A. McCammon. Brownian dynamics with hydrodynamic interactions. The Journal of Chemical Physics, 69(4):1352–1360, aug 1978. doi:10.1063/1.436761.
77: Eric Dickinson, Stuart A. Allison, and J. Andrew McCammon. Brownian dynamics with rotation–translation coupling. J. Chem. Soc., Faraday Trans. 2, 81(4):591–601, 1985. doi:10.1039/f29858100591.
78: R B Jones and P N Pusey. Dynamics of suspended colloidal spheres. Annual Review of Physical Chemistry, 42(1):137–169, oct 1991. doi:10.1146/annurev.pc.42.100191.001033.
79: David Baraff. Physically based modeling: rigid body simulation. SIGGRAPH Course Notes, 2001. doi:10.1145/97880.97881.
80: Ioana M. Ilie, Wouter K. den Otter, and Wim J. Briels. A coarse grained protein model with internal degrees of freedom. application to $\less $i$\greater $$\upalpha $$\less $/i$\greater $-synuclein aggregation. The Journal of Chemical Physics, 144(8):085103, feb 2016. doi:10.1063/1.4942115.
81: William Rowan Hamilton. II. $\less $i$\greater $on quaternions$\mathsemicolon $ or on a new system of imaginaries in algebra$\less $/i$\greater $. The London, Edinburgh, and Dublin Philosophical Magazine and Journal of Science, 25(163):10–13, jul 1844. doi:10.1080/14786444408644923.
82: Guillaume Chevrot, Konrad Hinsen, and Gerald R. Kneller. Model-free simulation approach to molecular diffusion tensors. The Journal of Chemical Physics, 139(15):154110, oct 2013. doi:10.1063/1.4823996.
83: V. Bloomfield, W. O. Dalton, and K. E. Van Holde. Frictional coefficients of multisubunit structures. i. theory. Biopolymers, 5(2):135–148, feb 1967. doi:10.1002/bip.1967.360050202.
84: L. Hu, G.M. Hu, Z.Q. Fang, and Y. Zhang. A new algorithm for contact detection between spherical particle and triangulated mesh boundary in discrete element method simulations. International Journal for Numerical Methods in Engineering, 94(8):787–804, mar 2013. doi:10.1002/nme.4487.
85: Daniel T. Gillespie. Exact stochastic simulation of coupled chemical reactions. The Journal of Physical Chemistry, 81(25):2340–2361, dec 1977. doi:10.1021/j100540a008.
86: Johannes Schöneberg and Frank Noé. ReaDDy - a software for particle-based reaction-diffusion dynamics in crowded cellular environments. PLoS ONE, 8(9):e74261, sep 2013. doi:10.1371/journal.pone.0074261.
87: Konrad Polthier and Markus Schmies. Straightest geodesics on polyhedral surfaces. In ACM SIGGRAPH 2006 Courses on - SIGGRAPH \textquotesingle 06. ACM Press, 2006. doi:10.1145/1185657.1185664.
88: Keenan Crane, Clarisse Weischedel, and Max Wardetzky. The heat method for distance computation. Communications of the ACM, 60(11):90–99, oct 2017. doi:10.1145/3131280.
89: P. Trettner, D. Bommes, and L. Kobbelt. Geodesic distance computation via virtual source propagation. Computer Graphics Forum, 40(5):247–260, aug 2021. doi:10.1111/cgf.14371.
90: Jorge R. Espinosa, Jerelle A. Joseph, Ignacio Sanchez-Burgos, Adiran Garaizar, Daan Frenkel, and Rosana Collepardo-Guevara. Liquid network connectivity regulates the stability and composition of biomolecular condensates with many components. Proceedings of the National Academy of Sciences, 117(24):13238–13247, jun 2020. doi:10.1073/pnas.1917569117.
91: H. J. C. Berendsen, J. P. M. Postma, W. F. van Gunsteren, A. DiNola, and J. R. Haak. Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics, 81(8):3684–3690, oct 1984. doi:10.1063/1.448118.
92: J. Garc\'ıa de la Torre, Stephen E. Harding, and Beatriz Carrasco. Calculation of NMR relaxation, covolume, and scattering-related properties of bead models using the SOLPRO computer program. European Biophysics Journal, 28(2):119–132, jan 1999. doi:10.1007/s002490050191.
93: José Garc\'ıa de la Torre and Álvaro Ortega. HYDRO suite of computer programs for solution properties of rigid macromolecules. In Encyclopedia of Biophysics, pages 1002–1006. Springer Berlin Heidelberg, 2013. doi:10.1007/978-3-642-16712-6_291.
94: Radek Erban and S Jonathan Chapman. Stochastic modelling of reaction–diffusion processes: algorithms for bimolecular reactions. Physical Biology, 6(4):046001, aug 2009. doi:10.1088/1478-3975/6/4/046001.
95: Marta Galanti, Duccio Fanelli, Sergey D. Traytak, and Francesco Piazza. Diffusion to capture and the concept of diffusive interactions. In Chemical Kinetics, pages 321–352. WORLD SCIENTIFIC (EUROPE), sep 2019. doi:10.1142/9781786347015_0014.
96: John Crank. The Mathematics of Diffusion. Oxford University Press, USA, 1980. ISBN 9780198534112.
97: Howard C. Berg. Random Walks in Biology. Princeton University Press, jan 1984. doi:10.1515/9781400820023.
98: Osman N. Yogurtcu and Margaret E. Johnson. Theory of bi-molecular association dynamics in 2d for accurate model and experimental parameterization of binding rates. The Journal of Chemical Physics, 143(8):084117, aug 2015. doi:10.1063/1.4929390.
99: Andrij Trokhymchuk, Ivo Nezbeda, Jan Jirsák, and Douglas Henderson. Hard-sphere radial distribution function again. The Journal of Chemical Physics, 123(2):024501, jul 2005. doi:10.1063/1.1979488.
100: Fu-Ming Tao, Yuhua Song, and E. A. Mason. Derivative of the hard-sphere radial distribution function at contact. Physical Review A, 46(12):8007–8008, dec 1992. doi:10.1103/physreva.46.8007.
101: McDonald Ian R Hansen Jean-Pierre. Theory of Simple Liquids. Elsevier, 2013. doi:10.1016/c2010-0-66723-x.
102: Steven S Andrews. Smoldyn: particle-based simulation with rule-based modeling, improved molecular interaction and a library interface. Bioinformatics, 33(5):710–717, dec 2016. doi:10.1093/bioinformatics/btw700.
103: Matthew J. Varga, Yiben Fu, Spencer Loggia, Osman N. Yogurtcu, and Margaret E. Johnson. NERDSS: a nonequilibrium simulator for multibody self-assembly at the cellular scale. Biophysical Journal, 118(12):3026–3040, jun 2020. doi:10.1016/j.bpj.2020.05.002.
104: Frank Noé, Alexandre Tkatchenko, Klaus-Robert Müller, and Cecilia Clementi. Machine learning for molecular simulation. Annual Review of Physical Chemistry, 71(1):361–390, apr 2020. doi:10.1146/annurev-physchem-042018-052331.
105: Tihamér Geyer. Many-particle brownian and langevin dynamics simulations with the brownmove package. BMC Biophysics, apr 2011. doi:10.1186/2046-1682-4-7.
106: Ian Snook. The Langevin and Generalised Langevin Approach to the Dynamics of Atomic, Polymeric and Colloidal Systems. Elsevier, 2007. doi:10.1016/b978-0-444-52129-3.x5000-7.
107: Uwe Winter and Tihame\'r Geyer. Coarse grained simulations of a small peptide: effects of finite damping and hydrodynamic interactions. The Journal of Chemical Physics, 131(10):104102, 2009. doi:10.1063/1.3216573.
108: Jose Garcia De La Torre and Victor A. Bloomfield. Hydrodynamics of macromolecular complexes. II. rotation. Biopolymers, 16(8):1765–1778, aug 1977. doi:10.1002/bip.1977.360160812.
109: C. W. Oseen. Neuere methoden und ergebnisse in der Hydrodynamik. Akadem. Verlagsges. Leipzig, 1927.