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MCell4 with BioNetGen: A Monte Carlo simulator of rule-based reaction-diffusion systems with Python interface.
Husar, Adam; Ordyan, Mariam; Garcia, Guadalupe C; Yancey, Joel G; Saglam, Ali S; Faeder, James R; Bartol, Thomas M; Kennedy, Mary B; Sejnowski, Terrence J.
Afiliação
  • Husar A; Computational Neurobiology Lab, Salk Institute for Biological Studies, La Jolla, California, United States of America.
  • Ordyan M; Institute for Neural Computations, University of California, San Diego, La Jolla, California, United States of America.
  • Garcia GC; Computational Neurobiology Lab, Salk Institute for Biological Studies, La Jolla, California, United States of America.
  • Yancey JG; Computational Neurobiology Lab, Salk Institute for Biological Studies, La Jolla, California, United States of America.
  • Saglam AS; Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
  • Faeder JR; Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
  • Bartol TM; Computational Neurobiology Lab, Salk Institute for Biological Studies, La Jolla, California, United States of America.
  • Kennedy MB; Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.
  • Sejnowski TJ; Computational Neurobiology Lab, Salk Institute for Biological Studies, La Jolla, California, United States of America.
PLoS Comput Biol ; 20(4): e1011800, 2024 Apr.
Article em En | MEDLINE | ID: mdl-38656994
ABSTRACT
Biochemical signaling pathways in living cells are often highly organized into spatially segregated volumes, membranes, scaffolds, subcellular compartments, and organelles comprising small numbers of interacting molecules. At this level of granularity stochastic behavior dominates, well-mixed continuum approximations based on concentrations break down and a particle-based approach is more accurate and more efficient. We describe and validate a new version of the open-source MCell simulation program (MCell4), which supports generalized 3D Monte Carlo modeling of diffusion and chemical reaction of discrete molecules and macromolecular complexes in solution, on surfaces representing membranes, and combinations thereof. The main improvements in MCell4 compared to the previous versions, MCell3 and MCell3-R, include a Python interface and native BioNetGen reaction language (BNGL) support. MCell4's Python interface opens up completely new possibilities for interfacing with external simulators to allow creation of sophisticated event-driven multiscale/multiphysics simulations. The native BNGL support, implemented through a new open-source library libBNG (also introduced in this paper), provides the capability to run a given BNGL model spatially resolved in MCell4 and, with appropriate simplifying assumptions, also in the BioNetGen simulation environment, greatly accelerating and simplifying model validation and comparison.
Assuntos

Texto completo: 1 Temas: ECOS / Financiamentos_gastos Bases de dados: MEDLINE Assunto principal: Software / Método de Monte Carlo Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Temas: ECOS / Financiamentos_gastos Bases de dados: MEDLINE Assunto principal: Software / Método de Monte Carlo Idioma: En Revista: PLoS Comput Biol Assunto da revista: BIOLOGIA / INFORMATICA MEDICA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos