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Figure 2.
Structure of the stochastic model for binary gene induction. Reactions enclosed in the box were simulated with Gillespie's exact method (see supporting material for reaction details). The reaction volume, i.e., the nucleus volume, was 100 μm3. TA: transcription activator. Φ represents RNA and protein degradation. Simulations started with 1 copy of inactive promoter, 0 ~ 512 copies of TA (equivalent to 0 ~ 8 nM), and 0 copies of all other molecule species. ki, kif and kib, for i = 1, 2, ..., 7, are stochastic reaction constants (k2f and k'2f are the TA-dependent and TA-independent activation rates of the promoter, respectively; k5 = In 2/
, k7 = In 2/
, where and are RNA and protein half-lives, respectively). s is protein detection sensitivity. Unless otherwise indicated, reaction constants k1f, k1b, k2f, k'2f, k3f, k3b, k4 and k6 were fixed for all simulations (k1f, k3f = 1.12 × 10-4; k1b, k3b = 1.48 × 10-2; k2f = 1.67 × 10-4; k'2f = 1 × 10-9; k2b = 3.33 × 10-5; k4 = 5.56 × 10-3; k6 = 4.17 × 10-3; unit = s-1). Background noise followed normal distribution N(10, 32) excluding values less than 1.
, k7 = In 2/, where and are RNA and protein half-lives, respectively). s is protein detection sensitivity. Unless otherwise indicated, reaction constants k1f, k1b, k2f, k'2f, k3f, k3b, k4 and k6 were fixed for all simulations (k1f, k3f = 1.12 × 10-4; k1b, k3b = 1.48 × 10-2; k2f = 1.67 × 10-4; k'2f = 1 × 10-9; k2b = 3.33 × 10-5; k4 = 5.56 × 10-3; k6 = 4.17 × 10-3; unit = s-1). Background noise followed normal distribution N(10, 32) excluding values less than 1.Zhang et al. Theoretical Biology and Medical Modelling 2006 3:18 doi:10.1186/1742-4682-3-18
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