Abstract
One of the major challenges in modern biology is to understand how the molecular components of a living cell operate in a highly noisy environment. What are the specific sources of noise in a cell? How do cells attenuate the effects of noise in order to exhibit reliable behavior (robustness to noise)? In particular, how does a stochastic genotype result in a reliable phenotype through development? How does the noisy, crowded environment of a cell affect diffusive transport? How do molecular machines convert chemical energy to work? What are the physical limits of biochemical signaling, such as the sensitivity of biochemical sensors to environmental signals? Under what circumstances can a cell exploit noise to enhance its performance or the survival of its host organism? What is the role of self-organization in the formation and maintenance of subcellular structures such as the cytoskeleton? The goal of this book is to use the theory of stochastic processes and non-equilibrium systems to investigate these types of biological questions at the cellular level; analogous questions also hold at the multicellular level but are not addressed in this book since they would double its length! One can view the book either as an introduction to stochastic processes using cell biology as the motivating application or, conversely, as an introduction to mathematical cell biology with an emphasis on stochastic processes.
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References
Alberts, B., Johnson, A., Lewis, J., Raff, M., Walter, K.R.: Molecular Biology of the Cell, 5th edn. Garland, New York (2008)
Allen, L.J.S.: An Introduction to Stochastic Processes with Applications to Biology, 2nd edn. Chapman and Hall/CRC, Boca Raton (2010)
Axelrod, D., Koppel, D.E., Schlessinger, J., Elson, E., Webb, W.W.: Mobility measurement by analysis of fluorescence photobleaching recovery kinetics. Biophys. J. 16, 1055–1069 (1976)
Bialek, W.: Biophysics. Princeton University Press, Princeton (2012)
Chandler, D.: Introduction to modern statistical mechanics. Oxford University Press, Oxford (1987)
Choquet, D., Triller, A.: The role of receptor diffusion in the organization of the postsynaptic membrane. Nat. Rev. Neurosci. 4, 251–265 (2003)
Elowitz, M.B., Levine, A.J., Siggia, E.D., Swain, P.S.: Stochastic gene expression in a single cell. Science 297, 1183–1186 (2002)
Gardiner, C.W.: Handbook of Stochastic Methods, 4th edn. Springer, Berlin (2009)
Grimmett, G.R., Stirzaker, D.R.: Probability and Random Processes, 3rd edn. Oxford University Press, Oxford (2001)
Howard, J.: Mechanics of Motor Proteins and the Cytoskeleton. Sinauer, Sunderland (2001)
Huber, F., Schnauss, J., Ronicke, S., Rauch, P., Muller, K., Futterer, C., Kas, J.E.: Emergent complexity of the cytoskeleton: from single filaments to tissue. Adv. Phys. 62, 1–12 (2013)
Jackson, M.B.: Molecular and Cellular Biophysics. Cambridge University Press, Cambridge (2006)
Kaern, M., Elston, T.C., Blake, W.J., Collins, J.J.: Stochasticity in gene expression: from theories to phenotypes. Nat. Rev. Genet. 6, 451–464 (2005)
Kardar, M.: Statistical Physics of Particles. Cambridge University Press, Cambridge (2007)
Keener, J.P., Sneyd, J.: Mathematical Physiology I: Cellular Physiology, 2nd edn. Springer, New York (2009)
Krapivsky, P.L., Redner, S., Ben-Naim, E.: A Kinetic View of Statistical Physics. Cambridge University Press, Cambridge (2010)
Kusumi, A., Sako, Y., Yamamoto, M.: Confined lateral diffusion of membrane receptors as studied by single particle tracking (nanovid microscopy): effects of calcium-induced differentiation in cultured epithelial cells. Biophys. J. 65, 2021–2040 (1993)
Lippincott-Schwartz, J., Phair, R.D.: Lipids and cholesterol as regulators of traffic in the endomembrane system. Annu. Rev. Biophys. 39, 559–578 (2010)
Lippincott-Schwartz, J., Roberts, T.H., Hirschberg, K.: Secretory protein trafficking abd organelle dynamics in living cells. Annu. Rev. Cell Dev. Biol. 16, 557–589 (2000)
Lyons, L.: Bayes and Frequentism: a particle physicist’s perspective. Contemp. Phys. 54, 1–16 (2013)
Maheshri, N., O’Shea, E.K.: Living with noisy genes: how cells function reliably with inherent variability in gene expression. Annu. Rev. Biophys. Biomol. Struct. 36, 413–434 (2007)
Misteli, T.: Self-organization in cell architecture. J. Cell Biol. 155, 181–186 (2001)
Mitchison, T.J.: Self-organization of polymer-motor systems in the cytoskeleton. Phil. Trans. Roy. Soc. Lond. B Biol. Sci. 336, 99–106 (1992)
Murray, J.D.: Mathematical Biology, vols. I and II, 3rd edn. Springer, Berlin (2008)
Nedelec, F., Surrey, T., Maggs, A.C., Leibler, S.: Self-organization of microtubules and motors. Nature 389, 305–308 (1997)
Nicolis, G., Prigogine, I.: Self-organization in nonequilibrium systems, 512 pp. Wiley, New York (1977)
Oksendal, B.: Stochastic Differential Equations: An Introduction with Applications, 5th edn. Springer, New York (1998)
Paulsson, J.: Models of stochastic gene expression. Phys. Life Rev. 2, 157–175 (2005)
Phillips, R., Kondev, J., Theriot, J., Garcia, H.: Physical Biology of the Cell, 2nd edn. Garland Science, New York (2012)
Raj, A., van Oudenaarden, A.: Nature, nurture, or chance: stochastic gene expression and its consequences Cell 135, 216–226 (2008)
Reits, E.A., Neefjes, J.J.: From fixed to FRAP: measuring protein mobility and activity in living cells. Nat. Cell Biol. 3, E145–E147 (2001)
Rook, M.S., Lu, M., Kosik, K.S.: CamKIIα 3’ untranslated regions-directed mRNA translocation in living neurons: visualization by GFP linkage. J. Neurosci. 20, 6385–6393 (2000)
Sanchez, A., Choubey, S., Kondev, J.: Regulation of noise in gene expression. Annu. Rev. Biophys. 42, 469–491 (2013)
Saxton, M.J., Jacobson, K.: Single-particle tracking: applications to membrane dynamics. Annu. Rev. Biophys. Biomol. Struct. 26, 373–399 (1997)
Schnapp, B.J., Gelles, J., Sheetz, M.P.: Nanometer-scale measurements using video light microscopy. Cell Motil. Cytoskeleton 10, 47–53 (1988)
Schnitzer, M., Visscher, K., Block, S.: Force production by single kinesin motors. Nat. Cell Biol. 2, 718–723 (2000)
Schuss, Z.: Theory and applications of stochastic processes: an analytical approach. In: Applied Mathematical Sciences, vol. 170. Springer, New York (2010)
Thattai, M., van Oudenaarden, A.: Intrinsic noise in gene regulatory networks. Proc. Natl. Acad. Sci. USA 98, 8614–8619 (2001)
Triller, A., Choquet, D.: New concepts in synaptic biology derived from single-molecule imaging. Neuron 59, 359–374 (2008)
Turing, A.M.: The chemical basis of morphogenesis. Philos. Trans. Roy. Soc. Lond. B 237, 37–72 (1952)
van Kampen, N.G.: Stochastic Processes in Physics and Chemistry. North-Holland, Amsterdam (1992)
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Bressloff, P.C. (2014). Introduction. In: Stochastic Processes in Cell Biology. Interdisciplinary Applied Mathematics, vol 41. Springer, Cham. https://doi.org/10.1007/978-3-319-08488-6_1
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