Abstract
We propose a new exact stochastic rejection-based simulation algorithm for biochemical reactions and extend it to systems with delays. Our algorithm accelerates the simulation by pre-computing reaction propensity bounds to select the next reaction to perform. Exploiting such bounds, we are able to avoid recomputing propensities every time a (delayed) reaction is initiated or finished, as is typically necessary in standard approaches. Propensity updates in our approach are still performed, but only infrequently and limited for a small number of reactions, saving computation time and without sacrificing exactness. We evaluate the performance improvement of our algorithm by experimenting with concrete biological models. © 2014 AIP Publishing LLC.
Original language | English |
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Journal | Journal of Chemical Physics |
Volume | 141 |
Issue number | 13 |
DOIs | |
Publication status | Published - 2014 |
MoE publication type | A1 Journal article-refereed |
Keywords
- Biochemical reactions
- Stochastic noise, folic acid, algorithm
- biochemistry
- biological model
- chemical model
- computer simulation
- human
- metabolism
- neoplasm
- signal transduction
- statistics, Algorithms
- Biochemical Processes
- Computer Simulation
- Folic Acid
- Humans
- MAP Kinase Signaling System
- Models, Biological
- Models, Chemical
- Neoplasms
- Stochastic Processes