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Mesoscopic Stochastic Spatial Simulations of Biochemical Networks

Mesoscopic Stochastic Spatial Simulations of Biochemical Networks. CellMath presentation by: Jordi Vidal Rodriguez. Goals. Simulations of biochemical networks… Space : for concentration inhomogeneities Stochastic : to account for molecular fluctuations

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Mesoscopic Stochastic Spatial Simulations of Biochemical Networks

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  1. Mesoscopic Stochastic Spatial Simulationsof Biochemical Networks CellMath presentation by: Jordi Vidal Rodriguez

  2. Goals • Simulations of biochemical networks… • Space: for concentration inhomogeneities • Stochastic: to account for molecular fluctuations • Mesoscopic: to cope with enormous number of molecules CellMath presentation

  3. Suitable Problems to Solve • Few particle systems • But how much is few? • Spatial inhomogeneity • Membranes are sources of concentration gradients • Prokaryotic cells • Simple cytosol that allows mesoscopic simulations • Pathways: • Oscillators, bifurcations, signalling,…? CellMath presentation

  4. Current Approach • Local Reaction with Gillespie method • Multiparticle, multispecies Diffusion • Membrane diffusion • Membrane is 1 site thick • Molecular fluctuations captured by both method. But how accurate are in this configuration? CellMath presentation

  5. Sources of Error • Membrane surface • Current model doesn’t simulate a surface • The site is still homogeneous affecting both • Reaction: homogeneous sub-volume • Diffusion: center of mass of particles in the center of site’s sub-volume • 2D-3D geometries CellMath presentation

  6. Measurements of Error Membrane site time evolution (Reaction) Profile evolution in time (L=20) CellMath presentation

  7. PTS pathway Simple case 2D circular domain CellMath presentation

  8. Current Activities • Reproduce PTS results • 3D geometries • Diffusion in 3D + Membrane diffusion • Arbitrary geometries (sphere, rods,…) • Lattice size effects • On molecular fluctuations (are thermodynamically correct?) • Membrane RD • Ways to improve membrane processes’ accuracy without compromising the mesoscopic model CellMath presentation

  9. Other Simulators of Interest • Smoldyn • StochSim, with membrane reactions! • VirtualCell • Going to include stochastic algorithm • E-Cell • Multi-algorithm, multi-scale • GENESIS • Neuron simulators • COPASI • Gillespie, inspired in Gepasi (Shall we expect stochastic control analysis?) CellMath presentation

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