Gillespie Stochastic Simulation is a computational algorithm in stochastic process modeling that exactly simulates the time evolution of a system of discrete chemical or biochemical reactions by generating statistically correct trajectories according to the underlying Markov jump process, distinguishing itself from deterministic or approximate stochastic methods by its precise adherence to the chemical master equation through random sampling of reaction times and types.
123
Publications
7.6K
Citations
306
Authors
143
Institutions
Publications per year
2017–2026
22
Variants
Gillespie Algorithm
Publications
123
1–5 of 123
Authors
306
- RE
4
h-index
- YC
4
h-index
- LP
4
h-index
- RCRussell Corbett‐Detig
University of California, Santa Cruz, United States
3 publications · 62 citations
3
h-index
- NG
3
h-index
1–5 of 306
Institutions
143
University of Oxford
Oxford, United Kingdom
5 h-index
13 publications
354 citations
University of California, Santa Barbara
Santa Barbara, United States
5 h-index
15 publications
2.3K citations
European Bioinformatics Institute
Cambridge, United Kingdom
4 h-index
15 publications
590 citations
Virginia Tech
Blacksburg, United States
4 h-index
13 publications
363 citations
University of Trento
Trento, Italy
4 h-index
7 publications
114 citations
University of Miami
Coral Gables, United States
4 h-index
7 publications
379 citations
University of California San Diego
San Diego, United States
4 h-index
8 publications
520 citations
Imperial College London
London, United Kingdom
4 h-index
7 publications
304 citations
1–8 of 143
Venues
- The Journal of Chemical Physics
25 publications · 3.1K citations
16
h-index
- BMC Bioinformatics
7 publications · 445 citations
7
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- PLoS ONE
6 publications · 122 citations
6
h-index
- Multiscale Modeling and Simulation
MMS · 5 publications · 214 citations
5
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- Bioinformatics
5 publications · 545 citations
5
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1–5