Efficient Exact Stochastic Simulation of Chemical Systems with Many Species and Many Channels

By Michael A. Gibson, Jehoshua Bruck. 2000

1,789 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/93f4c2c3d20dd740e1259c27b11cf2214a2bd267

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Darren J. Wilkinson
2. Robert Schober
3. Roger Brent
4. Santiago Schnell
5. Christoph Schwab
6. Michael Nip
7. Mustafa Hani Khammash
8. Ron Shamir

In Genetics

1. Christoph Schwab
2. Michael Nip
3. Vladimir A. Kazeev
4. Mustafa Hani Khammash
5. Darren J. Wilkinson
6. Roger Brent
7. Santiago Schnell
8. Ron Shamir

In Molecular Biology

1. Christoph Schwab
2. Michael Nip
3. Vladimir A. Kazeev
4. Paul C. Bressloff
5. Kevin Burrage
6. Thomas E. Turner
7. Mustafa Hani Khammash
8. Darren J. Wilkinson

Citations in the corpus

• Stochastic reaction-diffusion simulation with MesoRD (2005, methodology): “The SmartCell software (Ander et al., 2004), which in some aspects is similar to MesoRD, therefore recently changed its simulation algorithm from NRM to NSM. 3 CONCLUSIONS The use of MesoRD is not limited to the realm of molecular biology.”
• An overview of spatial microscopic and accelerated kinetic Monte Carlo methods (2007, methodology): “The most recently introduced, next reaction method [125] is another efficient selection method (see also Sect.”
• Stochastic switching in biology: from genotype to phenotype (2017, methodology): “These include the next reaction method [109] and the modified next reaction method [4].”
• Modelling and analysis of gene regulatory networks (2008, background): “Although Gisbon and Bruck introduced a way to speed up SS”
• Channel Modeling for Diffusive Molecular Communication—A Tutorial Review (2018, methodology): “These include Gibson and Bruck’s next reaction method (see [135]).”
• Direct Solution of the Chemical Master Equation Using Quantized Tensor Trains (2014, background): “A second broad class of methods are the kinetic Monte Carlo approaches which instead seek to produce either exact or approximate realizations of the underlying Markov process [3,9,10].”
• Stochastic approaches for modelling in vivo reactions (2004, methodology): “We discuss some further streamlining of the algorithm by Gibson and Bruck (2000), Gillespie (2001), Burrage and Tian (2003), Rathinam et al. (2003) and Tian and Burrage (2004a) leading to greater computational efficiency.”
• Stochastic modelling for quantitative description of heterogeneous biological systems (2009, methodology): “Although there are alternative exact simulation algorithms, such as the next reaction method”
• Modeling and Simulation of Genetic Regulatory Systems: A Literature Review (2002, neutral): “Gibson and Bruck (2000) have proposed various improvements of the Gillespie algorithm directed at reducing the computational complexity of the procedure.”
• Simulating the evolution of soot mixing state with a particle-resolved aerosol model (2008, neutral): “Gibson and Bruck [2000] developed the Next Reaction Method for efficient exact sampling, which stores and reuses event calculations for efficiency.”