Biology Reference
In-Depth Information
59.
Alfonsi A, Cancès E, Turinici G,
et al
. (2005) Adaptive simulation of hybrid
stochastic and deterministic models for biochemical systems. In: Cancès E,
Gerbeau JF (eds.).
ESAIM: Proceedings
, Vol. 14, pp. 1-13.
60.
Salis H, Sotiropoulos V, Kaznessis YN. (2006) Multiscale Hy3S: hybrid
stochastic simulation for supercomputers.
BMC Bioinformatics
7
: 93-112.
61.
Gillespie DT. (1976) A general method for numerically simulating the
stochastic time evolution of coupled chemical reactions.
J Comput Phys
22
: 403-34.
62.
Gillespie DT. (1977) Exact stochastic simulation of coupled chemical reac-
tions.
J Phys Chem
81
: 2340-61.
63.
Gibson MA, Bruck J. (2000) Efficient exact stochastic simulation of chemical
systems with many species and many channels.
J Phys Chem A
104
: 1876-89.
64.
Stundzia A, Lumsden C. (1996) Stochastic simulation of coupled reaction-
diffusion processes.
J Comput Phys
127
: 196-207.
65.
Isaacson SA, Peskin CS. (2006) Incorporating diffusion in complex geometries
into stochastic chemical kinetics simulations.
SIAM J Sci Comput
28
: 47-74.
66.
Liu JS. (2001)
Monte Carlo Strategies in Scientific Computing
. Springer Series
in Statistics. New York, NY: Springer.
67.
Rubinstein RY, Kroese DP. (2007)
Simulation and the Monte Carlo Method
,
2nd ed. New York, NY: Wiley.
68.
Milizzano F, Saffman PG. (1977) The calculation of large Reynolds number
two-dimensional flow using discrete vortices with random walk.
J Comput Phys
23
: 380-92.
69.
Schweitzer F. (2003)
Brownian Agents and Active Particles
.
On the Emergence
of Complex Behavior in the Natural and Social Sciences
. Springer Series in
Synergetics. Berlin, Germany, Springer.
70.
Gaylord RJ, Nishidate K. (1996)
Modeling Nature:
Cellular Automata
Simulations with Mathematica
. New York, NY: Springer.
71.
Ilachinski A. (2001)
Cellular Automata
. Singapore
:
World Scientific
Publishing.
72.
Schiff JL. (2007)
Cellular Automata
:
A Discrete View of the World
. Wiley Series
in Discrete Mathematics and Optimization. Hoboken, NJ: Wiley Interscience.
73.
Terano T, Kita H, Kaneda T,
et al
. (2005)
Agent-based Simulation
:
From
Modeling Methodologies to Real-World Applications
. Tokyo, Japan: Springer.
74.
Mosler HJ, Schwarz K, Ammann F, Gutscher H. (2001) Computer simulation
as a method of further developing a theory: simulating the elaboration likeli-
hood model (ELM).
Pers Soc Psychol Rev
5
: 201-15.
75.
Kloeden PE, Platen E. (1992)
Numerical Solution of Stochastic Differential
Equations
. Stochastic Modeling and Applied Probability. Berlin, Germany:
Springer.
76.
Higham DJ. (2001) An algorithmic introduction to numerical simulation of
stochastic differential equations.
SIAM Rev
43
: 525-46.