000 03911nam a22004935i 4500
001 vtls000543728
003 RU-ToGU
005 20210922082624.0
007 cr nn 008mamaa
008 160915s2014 gw | s |||| 0|eng d
020 _a9783319084886
_9978-3-319-08488-6
024 7 _a10.1007/978-3-319-08488-6
_2doi
035 _ato000543728
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQH323.5
050 4 _aQH324.2-324.25
072 7 _aPDE
_2bicssc
072 7 _aMAT003000
_2bisacsh
082 0 4 _a570.285
_223
100 1 _aBressloff, Paul C.
_eauthor.
_9445611
245 1 0 _aStochastic Processes in Cell Biology
_helectronic resource
_cby Paul C. Bressloff.
260 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2014.
300 _aXVII, 679 p. 206 illus., 90 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aInterdisciplinary Applied Mathematics,
_x0939-6047 ;
_v41
505 0 _aIntroduction -- Diffusion in Cells: Random walks and Brownian Motion -- Stochastic Ion Channels -- Polymers and Molecular Motors -- Sensing the Environment: Adaptation and Amplification in Cells -- Stochastic Gene Expression and Regulatory Networks -- Transport Processes in Cells -- Self-Organization in Cells I: Active Processes -- Self-Organization in Cells II: Reaction-Diffusion Models -- The WKB Method and Large Deviation Theory -- Probability Theory and Martingales.
520 _aThis book develops the theory of continuous and discrete stochastic processes within the context of cell biology.  A wide range of biological topics are covered including normal and anomalous diffusion in complex cellular environments, stochastic ion channels and excitable systems, stochastic calcium signaling, molecular motors, intracellular transport, signal transduction, bacterial chemotaxis, robustness in gene networks, genetic switches and oscillators, cell polarization, polymerization, cellular length control, and branching processes. The book also provides a pedagogical introduction to the theory of stochastic process – Fokker Planck equations, stochastic differential equations, master equations and jump Markov processes, diffusion approximations and the system size expansion, first passage time problems, stochastic hybrid systems, reaction-diffusion equations, exclusion processes, WKB methods, martingales and branching processes, stochastic calculus, and numerical methods.   This text is primarily aimed at graduate students and researchers working in mathematical biology and applied mathematicians interested in stochastic modeling.  Applied probabilists and theoretical physicists should also find it of interest. It assumes no prior background in statistical physics and introduces concepts in stochastic processes via motivating biological applications.     The book is highly illustrated and contains a large number of examples and exercises that further develop the models and ideas in the body of the text. It is based on a course that the author has taught at the University of Utah for many years.
650 0 _amathematics.
_9566183
650 0 _aCytology.
_9269442
650 0 _aDistribution (Probability theory).
_9303731
650 1 4 _aMathematics.
_9566184
650 2 4 _aMathematical and Computational Biology.
_9411705
650 2 4 _aProbability Theory and Stochastic Processes.
_9303734
650 2 4 _aCell Biology.
_9302220
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aInterdisciplinary Applied Mathematics,
_9303743
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-08488-6
912 _aZDB-2-SMA
999 _c400959