Gillespie DT. A general method for numerically simulating the stochastic time evolution of coupled chemical reactions. J Comput Phys. 1976; 22(4):403–34. doi:10.1016/0021-9991(76)90041-3.

Adrews SS, Dinh T, Arkin AP. Stochastic models of biological processes. Encycl Complex Syst Sci. 2009:8730–49. doi:10.1007/978-0-387-30440-3_524.

Raj A, van Oudenaarden A. Nature, nurture, or chance: stochastic gene expression and its consequences. Cell. 2008; 135(2):216–26. doi:10.1016/j.cell.2008.09.050.

Golding I, Paulsson J, Zawilski SM, Cox EC. Real-time kinetics of gene activity in individual bacteria. Cell. 2005; 123(6):1025–36. doi:10.1016/j.cell.2005.09.031.

Weinberger LS, Burnett JC, Toettcher JE, Arkin AP, Schaffer DV. Stochastic gene expression in a lentiviral positive-feedback loop: HIV-1 Tat fluctuations drive phenotypic diversity,. Cell. 2005; 122(2):169–82. doi:10.1016/j.cell.2005.06.006.

Samoilov M, Plyasunov S, Arkin AP. Stochastic amplification and signaling in enzymatic futile cycles through noise-induced bistability with oscillations,. Proc Natl Acad Sci U S A. 2005; 102(7):2310–5. doi:10.1073/pnas.0406841102.

Moles CG, Mendes P, Banga JR. Parameter estimation in biochemical pathways: a comparison of global optimization methods. Genome Res. 2003:2467–74. doi:10.1101/gr.1262503..

Rodriguez-Fernandez M, Egea JA, Banga JR. Novel metaheuristic for parameter estimation in nonlinear dynamic biological systems. BMC Bioinformatics. 2006:483. doi:10.1186/1471-2105-7-483.

Bock HG, Kostina E, Schlöder JP. Numerical Methods for Parameter Estimation in Nonlinear Differential Algebraic Equations. GAMM-Mitteilungen. 2007; 30(2):376–408. doi:10.1002/gamm.200790024.

Marquardt DW. An algorithm for least-squares estimation of nonlinear parameters. J Soc Ind Appl Math. 1963; 11(2):431–41. doi:10.1137/0111030.

Zimmer C. Reconstructing the hidden states in time course data of stochastic models. Math Biosci. 2015; 269:117–29. doi:10.1016/j.mbs.2015.08.015.

Zimmer C, Sahle S. Deterministic inference for stochastic systems using multiple shooting and a linear noise approximation for the transition probabilities. IET Syst Biol. 2015:1–12. doi:10.1049/iet-syb.2014.0020.

Komorowski M, Costa MJ, Rand DA, Stumpf MPH. Sensitivity, robustness, and identifiability in stochastic chemical kinetics models. Proc Natl Acad Sci. 2011; 108(21):8645–50. doi:10.1073/pnas.1015814108.

Golightly A, Wilkinson DJ. Bayesian inference for stochastic kinetic models using a diffusion approximation. Biometrics. 2005; 61(3):781–8. doi:10.1111/j.1541-0420.2005.00345.x.

Tian T, Xu S, Gao J, Burrage K. Simulated maximum likelihood method for estimating kinetic rates in gene expression. Bioinformatics. 2007; 23(1):84–91. doi:10.1093/bioinformatics/btl552.

Boys RJ, Wilkinson DJ, Kirkwood TBL. Bayesian inference for a discretely observed stochastic kinetic model. Stat Comput. 2008; 18(2):125–35. doi:10.1007/s11222-007-9043-x.

Zechner C, Ruess J, Krenn P, Pelet S, Peter M, Lygeros J, Koeppl H. Moment-based inference predicts bimodality in transient gene expression. Proc Natl Acad Sci. 2012; 109(21):8340–345. doi:10.1073/pnas.1200161109.

Kügler P. Moment fitting for parameter inference in repeatedly and partially observed stochastic biological models. PLoS ONE. 2012; 7(8):1–15. doi:10.1371/journal.pone.0043001.

Miller-Jensen K, Skupsky R, Shah PS, Arkin AP, Schaffer DV. Genetic selection for context-dependent stochastic phenotypes: Sp1 and TATA mutations increase phenotypic noise in HIV-1 gene expression. PLoS Comput Biol. 2013; 9(7). doi:10.1371/journal.pcbi.1003135.

Poovathingal SK, Gunawan R. Global parameter estimation methods for stochastic biochemical systems,. BMC Bioinformatics. 2010; 11:414. doi:10.1186/1471-2105-11-414.

Efficient parameter identification for stochastic biochemical networks using a reduced-order realization - Hori, Y.; Khammash, M. H.; Hara, S. (European Control Conference, ECC, 2013)

Lillacci G, Khammash M. The signal within the noise: efficient inference of stochastic gene regulation models using fluorescence histograms and stochastic simulations. Bioinformatics. 2013; 29(18):2311–9. doi:10.1093/bioinformatics/btt380.

Ivashkiv LB, Donlin LT. Regulation of type I interferon responses,. Nat Rev Immunol. 2014; 14(1):36–49. doi:10.1038/nri3581.

Hu J, Sealfon SC, Hayot F, Jayaprakash C, Kumar M, Pendleton AC, Ganee A, Fernandez-Sesma A, Moran TM, Wetmur JG. Chromosome-specific and noisy IFNB1 transcription in individual virus-infected human primary dendritic cells. Nucleic acids Res. 2007; 35(15):5232–41. doi:10.1093/nar/gkm557.

Zhao M, Zhang J, Phatnani H, Scheu S, Maniatis T. Stochastic expression of the interferon- β gene. PLoS Biol. 2012; 10(1):1001249. doi:10.1371/journal.pbio.1001249.

Levin D, Harari D, Schreiber G. Stochastic receptor expression determines cell fate upon interferon treatment. Mol Cell Biol. 2011; 31(16):3252–66. doi:10.1128/MCB.05251-11.

Schneider WM, Chevillotte MD, Rice CM. Interferon-stimulated genes: a complex web of host defenses. Annu Rev Immunol. 2014; 32:513–45. doi:10.1146/annurev-immunol-032713-120231.

Vasquez K, Sigrist K, Kucherlapati R, Demant P, Dietrich WF, Agoulnik S, Plus S. IRF-7 is the master regulator of. Nature. 2005; 434(April):772–7. doi:10.1038/nature03419.1..

Honda K, Taniguchi T. IRFs: master regulators of signalling by Toll-like receptors and cytosolic pattern-recognition receptors. Nat Rev Immunol. 2006; 6(9):644–58. doi:10.1038/nri1900.

Rand U, Rinas M, Schwerk J, Nöhren G, Linnes M, Kröger A, Flossdorf M, Kály-Kullai K, Hauser H, Höfer T, Köster M. Multi-layered stochasticity and paracrine signal propagation shape the type-I interferon response. Mol Syst Biol. 2012; 584:584. doi:10.1038/msb.2012.17.

MATLAB version (R2015a); 2015.

Hoops S, Sahle S, Gauges R, Lee C, Pahle J, Simus N, Singhal M, Xu L, Mendes P, Kummer U. COPASI–a COmplex PAthway SImulator. Bioinformatics (Oxford, England). 2006; 22(24):3067–74. doi:10.1093/bioinformatics/btl485.

Gibson MA, Bruck J. Efficient exact stochastic simulation of chemical systems with many species and many channels. J Phys Chem A. 2000; 104(9):1876–89. doi:10.1021/jp993732q.

Balkay L. FCS data reader. MATLAB Central File Exchange. 2006.

Yoder N. peakfinder. MATLAB Central File Exchange. 2009.

Gillespie DT. The chemical langevin equation. J Chem Phys. 2000; 113(1):297–306. doi:10.1063/1.481811.

Gillespie DT. Stochastic simulation of chemical kinetics. Annu Rev Phys Chem. 2007; 58:35–55. doi:10.1146/annurev.physchem.58.032806.104637.

Strogatz SH. Nonlinear dynamics and chaos with applications to physics, biology, chemistry, and engineering. New York: Westview Press; 2000. doi:10.1137/1037077.

Clever algorithms nature-inspired programming recipes - Brownlee, J. (Lulu Enterprises, 2011)

Legewie S, Herzel H, Westerhoff HV, Blüthgen N. Recurrent design patterns in the feedback regulation of the mammalian signalling network. Mol Syst Biol. 2008; 4(1):190. doi:10.1038/msb.2008.29.

Ning S, Huye LE, Pagano JS. Regulation of the transcriptional activity of the IRF7 promoter by a pathway independent of interferon signaling. J Biol Chem. 2005; 280(13):12262–70. doi:10.1074/jbc.M404260200.

Litvak V, Ratushny AV, Lampano AE, Schmitz F, Huang AC, Raman A, Rust AG, Bergthaler A, Aitchison JD, Aderem A. A FOXO3-IRF7 gene regulatory circuit limits inflammatory sequelae of antiviral responses. Nature. 2012; 490(7420):421–5. doi:10.1038/nature11428.

Treatment interruption to boost specific HIV immunity in acute infection - Kaufmann, D. E.; Walker, B. D. (Curr Opin HIV AIDS, 2007)

Dobrzyński M, Nguyen LK, Birtwistle MR, von Kriegsheim A, Fernández AB, Cheong A, Kolch W, Kholodenko BN. Nonlinear signalling networks and cell-to-cell variability transform external signals into broadly distributed or bimodal responses. J R Soc Interface. 2014; 11(98):20140383. doi:10.1098/rsif.2014.0383.

Kaern M, Elston TC, Blake WJ, Collins JJ. Stochasticity in gene expression: from theories to phenotypes. Nat Rev Genet. 2005; 6(6):451–64. doi:10.1038/nrg1615.

Begitt A, Droescher M, Meyer T, Schmid CD, Baker M, Antunes F, Knobeloch KP, Owen MR, Naumann R, Decker T, Vinkemeier U. STAT1-cooperative DNA binding distinguishes type 1 from type 2 interferon signaling. Nat Immunol. 2014; 15(2):168–76. doi:10.1038/ni.2794.

Cherry JL, Adler FR. How to make a biological switch. J Theor Biol. 2000; 203(2):117–33. doi:10.1006/jtbi.2000.1068.

Craciun G, Tang Y, Feinberg M. Understanding bistability in complex enzyme-driven reaction networks. Proc Natl Acad Sci. 2006; 103(23):8697–702. doi:10.1073/pnas.0602767103.

Schwanhäusser B, Busse D, Li N, Dittmar G, Schuchhardt J, Wolf J, Chen W, Selbach M. Global quantification of mammalian gene expression control. Nature. 2011; 473(7347):337–42. doi:10.1038/nature10098.

Yang E, van Nimwegen E, Zavolan M, Rajewsky N, Schroeder M, Magnasco M, Darnell JE. Decay rates of human mrnas: correlation with functional characteristics and sequence attributes. Genome Res. 2003; 13(8):1863–72. doi:10.1101/gr.1272403.