StochKit: A Computational Framework for Multiscale Discrete Stochastic Simulation of Biochemical Systems | |||
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StochKit is an efficient, extensible stochastic
simulation framework developed in the C++ language that aims to make
stochastic simulation accessible to practicing biologists and chemists,
while remaining open to extension via new stochastic and multiscale
algorithms. The current version of StochKit includes the popular Gillespie
Stochastic Simulation Algorithm (SSA) Direct Method, our new Logarithmic
Direct Method which is considerably faster than the original Direct
Method, slow-scale SSA for multiscale problems, adaptive non-negativity
preserving explicit tau-leaping, and core modules for explicit, implicit
and trapezoidal tau-leaping methods. StochKit is part of a larger software effort, SSALIB, which is pursued in collaboration with Dr. Mark Stalzer and Dr. Michael Hucka of Caltech. StochKit is supported by grants from NIH, DOE, and the UCSB Institute for Biotechnologies (US Army).
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