04620nam 22007575 450 991015044870332120251113211224.03-319-45318-110.1007/978-3-319-45318-7(CKB)3710000000943208(DE-He213)978-3-319-45318-7(MiAaPQ)EBC4740941(PPN)197139078(EXLCZ)99371000000094320820161110d2016 u| 0engurnn#008mamaatxtrdacontentcrdamediacrrdacarrierSimple Mathematical Models of Gene Regulatory Dynamics /by Michael C. Mackey, Moisés Santillán, Marta Tyran-Kamińska, Eduardo S. Zeron1st ed. 2016.Cham :Springer International Publishing :Imprint: Springer,2016.1 online resource (XIV, 124 p. 20 illus. in color.)Lecture Notes on Mathematical Modelling in the Life Sciences,2193-47973-319-45317-3 Includes bibliographical references and index.Introduction -- Part I Deterministic Modeling Techniques -- 1.Generic deterministic models of prokaryotic gene regulation -- 2.General dynamic considerations -- Part II Dealing with Noise -- 3.Master equation modeling approaches -- 4.Noise effects in gene regulation: Intrinsic versus extrinsic -- Part III Specific Examples -- 5.The lactose operon -- 6.The tryptophan operon -- 7.The Lysis-Lysogeny Switch -- Index -- References.This is a short and self-contained introduction to the field of mathematical modeling of gene-networks in bacteria. As an entry point to the field, we focus on the analysis of simple gene-network dynamics. The notes commence with an introduction to the deterministic modeling of gene-networks, with extensive reference to applicable results coming from dynamical systems theory. The second part of the notes treats extensively several approaches to the study of gene-network dynamics in the presence of noise—either arising from low numbers of molecules involved, or due to noise external to the regulatory process. The third and final part of the notes gives a detailed treatment of three well studied and concrete examples of gene-network dynamics by considering the lactose operon, the tryptophan operon, and the lysis-lysogeny switch. The notes contain an index for easy location of particular topics as well as an extensive bibliography of the current literature. The target audience of these notes are mainly graduates students and young researchers with a solid mathematical background (calculus, ordinary differential equations, and probability theory at a minimum), as well as with basic notions of biochemistry, cell biology, and molecular biology. They are meant to serve as a readable and brief entry point into a field that is currently highly active, and will allow the reader to grasp the current state of research and so prepare them for defining and tackling new research problems.Lecture Notes on Mathematical Modelling in the Life Sciences,2193-4797Molecular geneticsBiomathematicsBioinformaticsMathematicsDifferential equationsProbabilitiesMolecular GeneticsMathematical and Computational BiologyComputational and Systems BiologyApplications of MathematicsDifferential EquationsProbability TheoryMolecular genetics.Biomathematics.Bioinformatics.Mathematics.Differential equations.Probabilities.Molecular Genetics.Mathematical and Computational Biology.Computational and Systems Biology.Applications of Mathematics.Differential Equations.Probability Theory.511.8Mackey Michael Cauthttp://id.loc.gov/vocabulary/relators/aut60468Santillán Moisésauthttp://id.loc.gov/vocabulary/relators/autTyran-Kamińska Martaauthttp://id.loc.gov/vocabulary/relators/autZeron Eduardo Sauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910150448703321Simple Mathematical Models of Gene Regulatory Dynamics2093309UNINA