A bibliography for stochastic systems biology
(Somewhat out of date)
- Shimizu et al.: A spatially extended stochastic model of the bacterial chemotaxis signalling pathway. J. Mol. Biol. 2003;329:291-309. (E coli chemotaxis model)
- Gillespie. J. Phys. Chem. 81:2340-2361, 1977. Exact stochastic simulation of coupled chemical reactions.
- Ian Holmes adds: also J. Comput. Phys. 22:403-434? For citations see e.g...
- Laurenzi & Diamond: Monte Carlo simulation of the heterotypic aggregation kinetics of platelets and neutrophils. Biophys. J. 1999;77:1733-46.
- Arányi & Tóth: A full stochastic description of the Michaelis-Menten reaction for small systems. Acta Biochim. Biophys. Acad. Sci. Hung. 1977;12:375-88.
- Weinberger et al.: Stochastic gene expression in a lentiviral positive-feedback loop: HIV-1 Tat fluctuations drive phenotypic diversity. Cell 2005;122:169-82.
- Lai et al.: The sonic hedgehog signaling system as a bistable genetic switch. Biophys. J. 2004;86:2748-57.
- Stiles et al.: Miniature endplate current rise times less than 100 microseconds from improved dual recordings can be modeled with passive acetylcholine diffusion from a synaptic vesicle. Proc. Natl. Acad. Sci. U.S.A. 1996;93:5747-52. (use of MCell for synapse modelling)
- Samoilov et al.: Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations. Proc. Natl. Acad. Sci. U.S.A. 2005;102:2310-5.
Robustness and sensitivity:
- Barkai & Leibler: Robustness in simple biochemical networks. Nature 1997;387:913-7. (E coli chemotaxis robustness)
- Bray et al.: Receptor clustering as a cellular mechanism to control sensitivity. Nature 1998;393:85-8. (E coli chemotaxis receptor clustering)
- Duke & Bray: Heightened sensitivity of a lattice of membrane receptors. Proc. Natl. Acad. Sci. U.S.A. 1999;96:10104-8. (sensitivity of a receptor lattice)
- Ozbudak et al.: Regulation of noise in the expression of a single gene. Nat. Genet. 2002;31:69-73. (gene expression noise)
- Yi et al.: Robust perfect adaptation in bacterial chemotaxis through integral feedback control. Proc. Natl. Acad. Sci. U.S.A. 2000;97:4649-53. (robustness and fragility).
- Berg & Brown: Chemotaxis in Escherichia coli analysed by three-dimensional tracking. Nature 1972;239:500-4. (tracking of E. coli chemotaxis)
- Levin et al.: Origins of individual swimming behavior in bacteria. Biophys. J. 1998;74:175-81. (individual swimming behavior in E coli)
- Blake et al.: Noise in eukaryotic gene expression. Nature 2003;422:633-7. (noise in gene expression)
- Arkin et al.: Stochastic kinetic analysis of developmental pathway bifurcation in phage lambda-infected Escherichia coli cells. Genetics 1998;149:1633-48. (gene expression stochasticity in lambda)
- Schreiber et al.: Energy-efficient coding with discrete stochastic events. Neural Comput 2002;14:1323-46. (energy required for biological information transfer)
- Berg & Purcell: Physics of chemoreception. Biophys. J. 1977;20:193-219. (all about Brownian motion and chemotaxis)
- Berg. Random Walks in Biology, 1983 (a less technical book that expands on the Berg and Purcell paper)
- Futrelle. Trends Neurosci. 7:116-120, 1984 (diffusion of pheremones and capture by receptors)
- Kerr et al.: Local dispersal promotes biodiversity in a real-life game of rock-paper-scissors. Nature 2002;418:171-4. (rock-paper-scissors bacterial system)
- Wolf et al.: Diversity in times of adversity: probabilistic strategies in microbial survival games. J. Theor. Biol. 2005;234:227-53. (Stochastic Evolutionary Games)
- Rao et al.: Control, exploitation and tolerance of intracellular noise. Nature 2002;420:231-7.
- Elowitz et al.: Stochastic gene expression in a single cell. Science 2002;297:1183-6.
- Swain et al.: Intrinsic and extrinsic contributions to stochasticity in gene expression. Proc. Natl. Acad. Sci. U.S.A. 2002;99:12795-800.
- Blake et al.: Noise in eukaryotic gene expression. Nature 2003;422:633-7.
- McAdams & Arkin: Stochastic mechanisms in gene expression. Proc. Natl. Acad. Sci. U.S.A. 1997;94:814-9.
- Weinberger et al.: Stochastic gene expression in a lentiviral positive-feedback loop: HIV-1 Tat fluctuations drive phenotypic diversity. Cell 2005;122:169-82. (Stochastic gene expression in HIV)
Also see the O'Shea paper on yeast stochastics.
- Raser & O'Shea: Control of stochasticity in eukaryotic gene expression. Science 2004;304:1811-4.
The above list was in the most part suggested by Adam Arkin:
From: Ian Holmes Sent: Thursday, August 18, 2005 1:35 PM To: Adam Arkin Subject: Re: Langevin biology
After Ted's recent talk on stochastic resonance, you mentioned an example of stability analysis in a Langevin model system.
In my graduate class this fall, I'm hoping to touch on Langevin dynamics (the broad scope is "stochastic computational biology": mainly grammars and trees, but I'd like to mention stochastic biophysics).
Could you recommend one or two pithy biological analogues of the canonical models in classical stochastic physics (Langevin, Smoluchowski, Fokker-Planck etc) or of stochastic differential equations in general (Ito processes, Wiener, superprocesses, etc)?
From: Adam Arkin
Well-- the classical great example is E. coli chemotaxis with examples form Berg's Stochastic processes in Biology Book. Then there is a vast literature in neural stochastics, ion channel stochastics etc. There are spatial stochastic models of calcium waves in T-cells and cardiomyocytes. There are models with the OU process and immune cell motility. And then there is the new literature on stochastic gene expression and signaling.
Are there particular areas you are interested in?
As for the Langevin analysis I mentioned I'm attaching our PNAS paper on the subject and preprint on the "mistakes" made on going from the chemical master equation and the deterministic cellular kinetic equations.
Also-- below is short bibliography covering a number of topics....
Anyway-- tell me if this is what you needed or you want me to be more focused.