Literature DB >> 29303160

A MODELING AND SIMULATION LANGUAGE FOR BIOLOGICAL CELLS WITH COUPLED MECHANICAL AND CHEMICAL PROCESSES.

Endre Somogyi1, James A Glazier2.   

Abstract

Biological cells are the prototypical example of active matter. Cells sense and respond to mechanical, chemical and electrical environmental stimuli with a range of behaviors, including dynamic changes in morphology and mechanical properties, chemical uptake and secretion, cell differentiation, proliferation, death, and migration. Modeling and simulation of such dynamic phenomena poses a number of computational challenges. A modeling language describing cellular dynamics must naturally represent complex intra and extra-cellular spatial structures and coupled mechanical, chemical and electrical processes. Domain experts will find a modeling language most useful when it is based on concepts, terms and principles native to the problem domain. A compiler must then be able to generate an executable model from this physically motivated description. Finally, an executable model must efficiently calculate the time evolution of such dynamic and inhomogeneous phenomena. We present a spatial hybrid systems modeling language, compiler and mesh-free Lagrangian based simulation engine which will enable domain experts to define models using natural, biologically motivated constructs and to simulate time evolution of coupled cellular, mechanical and chemical processes acting on a time varying number of cells and their environment.

Entities:  

Keywords:  Biological Systems Modeling; Simulation; Spatial Hybrid Systems

Year:  2017        PMID: 29303160      PMCID: PMC5749416     

Source DB:  PubMed          Journal:  Symp Theory Model Simul


  7 in total

1.  Rule-based modeling of biochemical systems with BioNetGen.

Authors:  James R Faeder; Michael L Blinov; William S Hlavacek
Journal:  Methods Mol Biol       Date:  2009

Review 2.  How computational models can help unlock biological systems.

Authors:  G Wayne Brodland
Journal:  Semin Cell Dev Biol       Date:  2015-07-09       Impact factor: 7.727

3.  Transport dissipative particle dynamics model for mesoscopic advection-diffusion-reaction problems.

Authors:  Zhen Li; Alireza Yazdani; Alexandre Tartakovsky; George Em Karniadakis
Journal:  J Chem Phys       Date:  2015-07-07       Impact factor: 3.488

4.  ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

Authors:  Arne T Bittig; Adelinde M Uhrmacher
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2016-08-03       Impact factor: 3.710

5.  Detailed simulations of cell biology with Smoldyn 2.1.

Authors:  Steven S Andrews; Nathan J Addy; Roger Brent; Adam P Arkin
Journal:  PLoS Comput Biol       Date:  2010-03-12       Impact factor: 4.475

6.  Rule-based spatial modeling with diffusing, geometrically constrained molecules.

Authors:  Gerd Gruenert; Bashar Ibrahim; Thorsten Lenser; Maiko Lohel; Thomas Hinze; Peter Dittrich
Journal:  BMC Bioinformatics       Date:  2010-06-07       Impact factor: 3.169

7.  ReaDDy--a software for particle-based reaction-diffusion dynamics in crowded cellular environments.

Authors:  Johannes Schöneberg; Frank Noé
Journal:  PLoS One       Date:  2013-09-11       Impact factor: 3.240

  7 in total

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